Top 12 Potential PhD Viva Questions and How to Answer Them
Breathed a sigh of relief after submitting the PhD thesis you’ve burnt the midnight oil for? Not so soon! While submitting your thesis is a massive achievement, defending it decides whether you will receive the doctoral degree or not. Although every PhD viva examination is different, there are similarities in the types of questions asked at each. In this article, we shall discuss the most common and potential PhD viva questions and how to answer them.
Types of PhD Viva Questions
Generally, examiners prepare a series of questions for you to answer at the PhD viva voce examination. These questions are primarily based on your thesis. However, the questions asked in PhD viva examinations can be broadly grouped under four basic headings:
- General Questions
- Research Context and Methods
- Analysis and Findings
- Discussions and Conclusion/Implications
Therefore, while preparing for your PhD viva and defending your thesis , you must consider the types of questions you’re likely to be asked. This helps in practicing your answers in advance and not being baffled during the viva. Practicing how you would answer questions based on these four basic categories will take you a long way in your preparations.
Commonly Asked PhD Viva Questions and How to Answer Them
While sticking to answering the most commonly asked questions might sound simple, it is equally important to be prepared for counter questions. Furthermore, it’s easy to go off on a tangent due to nervousness. This leads to opening up other lines of enquiry from the examiners in areas you hadn’t probably expected to be questioned about.
Ideally, you aren’t expected to dictate your thesis as it is. Examiners are interested in knowing your understanding of the research, its methods, analysis and findings, conclusion and implications, etc.
Despite the differences in every PhD viva, you must be prepared to answer these common questions logically. Below are some popular PhD viva questions to prepare:
1. Tell me about yourself.
Introduce yourself and talk about your areas of interest related to research. More importantly, focus on the areas you are extremely positive about. Briefly speak about your past achievements without overwhelming the examiners and sounding boastful. Keep the introduction professional.
2. What is the reason for selecting this research question?
The response to this question is often generalized by saying that you are interested in the topic. However, examiners want to hear the specifications of your interest in the topic. You must plan your answer stating the most interesting aspect of your research and why did you choose the research question over another topic from the same or allied domain. Furthermore, cite certain instances that helped you in selecting the research topic and the particular field for your project.
3. What is the key focus of your research?
Remember that the answer to this question is not about summarizing your research. It involves talking about the area of primary focus of research. Most importantly, in order to demonstrate the viability of your research, it is essential to identify some of the key questions it addresses.
4. Did the research process go as per your plan or were there any unexpected circumstances that you had to deal with?
The purpose of this question is not only to see whether you can work as per your structured plan, but also to understand your readiness with backup plans in case of unforeseen situations. An ideal way to answer this is by clearly stating if the project went as per your predefined plan. Furthermore, be honest in mentioning if you were assisted by others in dealing with it, as it may lead to a new set of questioning from the examiners.
5. After completion of your research, which part of the process did you enjoy the most and why?
Remember that the examiners know about a PhD student’s stressful journey . Therefore, do not elaborate on the hardships that you went through during your research, unless asked otherwise. Emphasize on the aspects of the research project that you enjoyed and looked forward to every time you stepped in your laboratory. Describe how you developed interest in newer approaches to conduct research.
6. As a researcher, what change has this research brought in you?
This question demands a strong, progressive, and positive response. Remember your first day in the research laboratory and compare it to today. Identify the differences in your traits as a researcher. Mention how following, reading, and analyzing other researchers’ works have brought a positive change in you. Furthermore, address how you overcame your shortcomings as a researcher and upskilled yourself.
7. Summarize your thesis.
Be well versed with the entire project. Start by explaining why you selected the topic of your thesis and close your explanation by providing an optimum solution to the problem. You must prepare for 3 types of answers for this question. Prepare a 1-minute, 3-5 minutes, and 10-minute summary and use the correct one based on your audience at the viva.
8. What developments have you witnessed in this field since you began your doctorate? How did these developments change your research context?
Familiarize yourself with the advances in your field throughout your PhD. Mention works of researchers you have referred to while working on your project. Additionally, elaborate on how other researchers’ work influenced your research and directed you to finding results.
9. What original contribution has your thesis made to this field of study?
Answer this question by keeping in mind what was known before in published literature and what you have added as part of being awarded your PhD. Firstly, you must present a major piece of new information during your research project. Secondly, elaborate on how your research expands the existing literature. Thirdly, mention how your work is different from other researchers’ works that you referred. Finally, discuss how you developed a new product or improved an existing one.
10. How well did the study design work?
While answering this question, you must focus on how your planned methods and methodologies were executed. Furthermore, mention how you tackled difficulties in study design and concluded your research.
11. Elaborate on your main findings and how do they relate to literature in your field?
While answering this question, elaborate on how you evaluated the key findings in your research. Mention the key factors involved and the reason for choosing a particular process of evaluation. Furthermore, explain how your findings are related with the literature review of your project. Mention its significant contributions in your field of research. In addition, discuss how your research findings connect with your hypothesis as well as the conclusion of your research.
12. What is the strength and weakness of your research?
While you may want to impress the examiner by emphasizing on the strengths of your research, being aware of the weaknesses and planning a directional move to overcome them is also equally important. Hence, mention the strengths first and elaborate on how they connect with the key findings. Additionally, underline the limitations and the factors that could be transformed into strengths in future research.
How nervous were you while preparing for your PhD viva voce? Did you follow any specific tips to ace your PhD viva voce ? How important is it to prepare for these common PhD viva questions beforehand? Let us know how you prepared for your PhD viva voce in the comments section below! You can also visit our Q&A forum for frequently asked questions related to different aspects of research writing and publishing answered by our team that comprises subject-matter experts, eminent researchers, and publication experts.
Really useful in helping me put a plan / script together for my forthcoming viva. Some interesting questions that I hadn’t thought about before reading this article – the proof of the pudding will be how well the viva goes of course, but at least I now have a head start! Many thanks
Thank you, this is super helpful. I have my viva voce in a month and I’ll be using these questions as a guide
Well framed questions
This article has been incredibly helpful in preparing a plan and script for my upcoming viva. It introduced me to several intriguing questions I hadn’t considered before. The real test will be how well the viva goes, but at least I now have a head start. Thank you.
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Dr. Andrew Broad Computer Science CS710 Nasty PhD Viva Questions (Extract)
There are three reasons why PhD candidates have to have a viva: it is so the examiners can see:
- whether it is your own work;
- whether you understand what you did;
- whether it is worth a PhD (i.e. is a contribution to knowledge).
These are the points being examined (according to Alex Gray from the University of Cardiff):
- Understanding : that you're ready to become an independent researcher.
- Relationship to other work : that you have a command of your subject-area. Similarity to the work of others doesn't detract from novelty!
- Novelty - is your work publishable? If you have already published a couple of papers, that should be proof of sufficient originality. Don't panic about recent publications that are very similar to your work - the important thing is to be aware of them, and to know the differences between your work and theirs.
- What you have achieved , and that you are aware of its implications . What will it make a difference to?
- Demonstration of hypothesis (what you set out to achieve). How have you evaluated/tested your hypothesis? Always be prepared to reconsider your hypothesis if you end up demonstrating something else - it's vitally important that your results match your hypothesis, and that you have a convincing argument for this.
- Why did you do it the way you did? Not just your practical work, but everything. For example, your literature review should be focused towards your hypothesis.
Preparing for the Viva: Before you submit
It's crucial to get the philosophy of your thesis (as set out in your Chapter 1) absolutely correct, and clear in your mind by the time of the viva , because if the examiners find holes, they'll run rings round you.
They could ask you to explain/justify any statement in the thesis , so beware of baring nasty branches for clarification at the viva! Identify the contentious statements in the thesis, which you anticipate having to defend in the viva. A good supervisor will point out the contentious statements and grill you over them. Start a file of anticipated viva questions .
The conclusion chapter is a major one to focus on in anticipating viva questions - especially where you criticise your work!
Obviously, it's essential to know your own thesis thoroughly . I think it's a great idea to compile a brief summary of each section before you submit - enough to remind you of what's in each section, paragraph by paragraph or similar (my thesis summary is very different to, and shorter than, my thesis plan, where I basically wrote down all the points I could think of, then when I wrote it up, I added and deleted points, and changed the structure). Compiling a thesis summary before you submit has the advantages that you may spot strategic-level flaws in time to fix them, and will enable you to revise for the viva from the thesis summary rather than from the thesis itself.
Don't try to get the thesis perfect and free of minor corrections at the expense of delaying submission. It's almost certain that the examiners will find something to correct, anyway.
Preparing for the Viva: After you submit
The most important goal in preparing for the viva is to keep the subject alive in your head .
Try to anticipate the questions you'll be asked in your viva and keep working on a file of anticipated questions (both the generic questions listed on this web-page, and questions specific to particular sections of your thesis) and your answers. If you said anything without understanding it 100%, or anything you have doubts about having justified properly, add it to your viva file.
You can go into university after you've submitted your thesis and your registration has expired - doing some more practical work may (or may not) help to keep the subject alive in your head (you could do experiments and take printouts of the results to the viva).
However, the main preparation for the viva is reading . These are the things to prioritise:
- If your thesis contains mathematical formulae, check them carefully so that you're confident, by the time of the viva, that they're correct. If they're not correct, work it out in advance so that you're not flustered by mathematical mistakes at the viva.
- Be familiar with the references cited in your thesis , because that's the literature your examiners are most likely to ask you about. Read anything you have cited without reading (not that you should cite things without reading in the first place!).
- So make sure you're familiar with the literature - not everything you've read in the last three years, but the more important stuff.
- Look for recent review/survey papers of related areas. You need to be able to discuss the state of the art in any area related to your thesis.
- Recent publications tend to be particularly important (what are the recent developments in your field?), although they can't ask you about anything published after you submitted your thesis.
- Read the examiners' publications to get a feel for where they're coming from, what things they consider important, and which topics they consider relevant.
- Don't stop reading until after the viva.
It might be an idea to publish a paper or two between submitting your thesis and the viva - I wish I had done so. Try to write papers from different perspectives.
The time between submitting the thesis and the viva varies greatly. I submitted my thesis on 28th September 2001, and had my viva on 18th September 2002! My thesis was very long (390 pages including appendices), and there was a delay in finding a suitable external examiner, but above all you have to remember that your examiners will be busy with other things too!
The shortest time I've heard of between submission and viva is three weeks (different subject, different university).
They have to give you at least two weeks' notice before the viva. I got five weeks' notice. My internal examiner suggested a couple of dates, I chose 18th September and asked for 14:00 in IT406, and this was officially confirmed a few days later.
The Viva itself
The PhD viva is an open-book exam : you can bring any materials you want. Here is what I think one should bring to the viva:
- a copy of your thesis, obviously - you can stick yellow `post-it' notes on it (e.g. anticipated questions and answers), although I personally abhorred the idea of preparing from my thesis itself;
- your list of anticipated viva questions and your answers;
- printouts of the results of any post-submission experiments;
- the chapter-summaries you made for revision;
- all the notebooks you should have been keeping since the start of your research (the notebooks need to be indexed so that you can look things up);
- any papers such that when you reviewed them in the thesis, you regurgitated something they said blindly without really understanding it (in my case, I identified two such papers, but I brought a dozen potentially contentious papers to the viva);
- printouts of any files or emails containing useful ideas which you haven't documented elsewhere;
- tissues, paracetemol, &c. in case of any unexpected bouts of sneezing, headaches, &c.
At my viva, I gave a presentation (using slides) about some experiments I did after I submitted my thesis. But it's unusual for the candidate to give a presentation, and your supervisor should advise you if it is appropriate to do this. If you do give a presentation, be prepared to be flexible - I was asked to speed up and just give the highlights.
It is not the norm, in this department (I do not speak for other departments/universities), to be expected to give a practical demonstration of your work at the viva, but you could always offer to do so if you think it will help your cause (unlikely).
Anyone can attend a PhD viva, but only the examiners and the candidate can participate. (This means it may be a good idea to attend someone else's viva before your own, though I've never had the balls to gate-crash a viva! :-o )
Your supervisor should definitely attend your viva, although (s)he is usually not allowed to participate unless invited to do so by the examiners. It might be an idea to keep an eye on the body-language of your supervisor to see if you're going wrong! ;-)
A viva typically lasts two hours (but as long as it takes - mine lasted 2h22m), and a common approach is for the examiners to go through the thesis sequentially, asking questions.
Just because they ask a lot of questions doesn't mean you're going to fail. They don't give away the result before or during the viva, but you may be asked to wait around for the result at the end (about half an hour), so that they can explain the result to you - particularly if you have to resubmit your thesis (failure without the option of resubmission is very rare, and is not going to happen if you submit anything resembling a sensible thesis).
- Relax and enjoy it, if possible!
- Ideas should flow out from you without a lot of prompting.
- Listen carefully to the questions and take your time answering them.
- Answer your questions succinctly (a rough guideline is 2 to 3 minutes each - no 20-minute diatribes!). Avoid going off at a tangent.
- Try to make your answers initially inclusive (spot overlaps), analytical, and then if appropriate dismissive or point out the limitations - and the effects of these limits.
- Generic viva questions, such as the ones given in the section below, require imagination to answer well!
- Answers may utilise a wide variety of examples and domains. They are a test of your breadth of knowledge as well as depth of knowledge which is expected of a PhD student.
- If you don't understand the question, ask for clarification. Paraphrase the question in your own words and say, "is this what you mean?" State your assumptions.
- Treat vague questions as invitations to tell the examiners that you know your area and how it fits into related areas. Try to link the question to the questions you have anticipated and their stock answers. After writing a thesis, you should have one big, connected network of discussion in your head, so you need to jump in at the appropriate place for a given question.
- If they have a misconception about your work, try to pin it down and explain it.
- If you think the question is irrelevant, explain why you think it is irrelevant (it may be that you need to be more broad-minded).
- If you have any idea at all, say it.
- Say, "I can't answer this on the spot, but I should be able to work it out in my own time."
- If it's about literature you haven't come across, thank the questionner and ask for a reference.
Typical Viva Questions
Here are some generic viva-questions - you should instantiate each question for your particular thesis, and have a framework for answering it worked out before the viva.
I have tried to cluster related questions together here - they are not necessarily in order of importance, nor in the order that they are likely to be asked at the viva.
General Questions
- What is the area in which you wish to be examined? (particularly difficult and important if your thesis fits into several areas, or has several aspects, or seems to fit into an area of its own as mine does).
- In one sentence, what is your thesis? (Resist the temptation to run from the room!)
- What have you done that merits a PhD?
- Summarise your key findings.
- What are you most proud of, and why? This may be asked (again) towards the end of the viva.
- What's original about your work? Where is the novelty? Don't leave it to the examiners to make up their own minds - they may get it wrong!
- What are the contributions (to knowledge) of your thesis?
- How does your work relate to X?
- What do you know about the history of X?
- What is the current state of the art in X? (capabilities and limitations of existing systems) What techniques are commonly used? Where do current technologies fail such that you (could) make a contribution?
- How does/could your work enhance the state of the art in X?
- Who are the main `players' in X? (Hint: you should cluster together papers written by the same people) Who are your closest competitors?
- What do you do better than them? What do you do worse?
- Which are the three most important papers in X?
- What are the recent major developments in X?
- How do you expect X to progress over the next five years? How long-term is your contribution, given the anticipated future developments in X?
- What did you do for your MPhil, and how does your PhD extend it? Did you make any changes to the system you implemented for your MPhil?
- What are the strongest/weakest parts of your work?
- Where did you go wrong?
- Why have you done it this way? You need to justify your approach - don't assume the examiners share your views.
- What are the alternatives to your approach? What do you gain by your approach? What would you gain by approach X?
- Why didn't you do it this way (the way everyone else does it)? This requires having done extensive reading. Be honest if you never thought of the alternative they're suggesting, or if you just didn't get around to it. If you try to bluff your way out, they'll trap you in your own words.
- Looking back, what might you have done differently? This requires a thoughtful answer, whilst defending what you did at the time.
- How do scientists/philosophers carry out experiments?
- intrinsic evaluation : how have you demonstrated that it works, and how well it performs?
- extrinsic evaluation : how have you demonstrated its usefulness for a specific application context?
- What do your results mean?
- How would your system cope with bigger examples? Does it scale up? This is especially important if you have only run your system on `toy' examples, and they think it has `learned its test-data'.
- How do you know that your algorithm/rules are correct?
- How could you improve your work?
- What are the motivations for your research? Why is the problem you have tackled worth tackling?
- to other researchers?
- to industry?
- What is the implication of your work in your area? What does it change?
- How do/would you cope with known problems in your field? (e.g. combinatorial explosion)
- Have you solved the field's problem that you claim to have solved? For example, if something is too slow, and you can make it go faster - how much increase in speed is needed for the applications you claim to support?
- Is your field going in the right direction? For example, if everyone's been concentrating on speed, but the real issue is space (if the issue is time, you can just wait it out (unless it's combinatorially explosive), but if the issue is space, the system could fall over). This is kind of justifying why you have gone into the field you're working in.
- Who are your envisioned users? What use would your work be in situation X?
- How do your contributions generalise? To what extent would they generalise to systems other than the one you've worked on? Under what circumstances would your approach be useable? (Again, does it scale up?)
- Where will you publish your work? Think about which journals and conferences your research would best suit. Just as popular musicians promote their latest albums by releasing singles and going on tour, you should promote your thesis by publishing papers in journals and presenting them at conferences. This takes your work to a much wider audience; this is how academics establish themselves.
- Which aspects of your thesis could be published?
- What have you learned from the process of doing your PhD? Remember that the aim of the PhD process is to train you to be a fully professional researcher - passing your PhD means that you know the state of the art in your area and the directions in which it could be extended, and that you have proved you are capable of making such extensions.
- Where did your research-project come from? How did your research-questions emerge? You can't just say "my supervisor told me to do it" - if this is the case, you need to talk it over with your supervisor before the viva. Think out a succinct answer (2 to 5 minutes).
- Has your view of your research topic changed during the course of the research?
- You discuss future work in your conclusion chapter. How long would it take to implement X, and what are the likely problems you envisage? Do not underestimate the time and the difficulties - you might be talking about your own resubmission-order! ;-)
Particular Questions
Most of the viva will probably consist of questions about specific sections of your thesis, and the examiner should give a page-reference for each question. According to Alex Gray, these questions fall into six categories:
- Clarification. The examiners ask you to explain a particular statement in the thesis. In some cases, their lack of understanding may be due to a typo, e.g. "Why did you connect the client to the sewer?" Also, "not" is a small word which makes a big difference! ;-)
- Justification.
- Alternatives considered. Be honest if you didn't consider alternatives, otherwise you'll be digging a hole for yourself.
- Awareness of other work.
- Distinction from similar work. Especially recent publications where others are working in the same area - what are the similarities and differences between your work and theirs?
- Correction of errors (typos, technical errors, misleading statements, and so on).
Acknowledgements
Much of the material on this page comes from my supervisor Nick Filer , from CS700 / CS710 , from questions I've been asked at the end of various presentations I've given, and from my own viva (most of the questions there were thesis-specific). I added questions from the external websites given at the end of this document. I also updated this document in the light of Alex Gray's keynote speech, "Surviving the PhD Viva: An External Examiners Perspective" at the 2002 Research Students' Symposium .
If you can think of any viva-style questions that are not covered by the above, please do not hesitate to tell me, and I will consider them for inclusion on this page.
Finally, I found my own viva much less stressful than I thought it was going to be. The examiners know that it's an ordeal for anybody, so they should go out of their way to put you at your ease and make you feel comfortable. I was amazed how calm I was, even when I went back to hear the result. If you're worried about getting an `impossible' resubmission-order, remember it's not the examiners' job to set insurmountable hurdles - they want you to pass as soon as possible.
Common PhD Viva Questions (To Help You Prepare For Yours)
May 27, 2022
Capable of striking fear into the heart of even the most confident PhD student, the Viva looms large over the entire PhD journey. No matter whether the PhD is going well or causing problems, there’s always the viva to worry about.
Long story short, everyone is scared of the viva.
One thing that can help is knowing what to expect during the viva itself. That’s why we got in touch with Professor Peter Smith, who recently published The PhD Viva: How to Prepare for Your Oral Examination with Palgrave, and who has successfully supervised 60+ PhD and professional doctorate students and examined a further 50+ PhD students all over the world. We asked him what the most common questions are that students face during their vivas. Read his answer below.
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1. An Opening Question
The examiners will quite often start a viva with an opening question; perhaps something like this: “Spend five or ten minutes telling us about your work, what you have done, and what the contribution is” or “Summarise your work for us, in a single sentence.” A question like this gives you an opportunity to explain your work up front, breaks the ice, settles you in and gets you talking. Making a contribution is the most important element of the PhD thesis. It is very likely that you will be questioned about this.
2. The aims, objectives, research questions, and hypotheses
In your thesis you will have set out the purpose of your work. Depending on the discipline that you working in, you may have called this an aim (with accompanying objectives), a question (or a series of questions) or an hypothesis (or a series of hypotheses). It doesn’t matter what you have called this in your thesis; you need to be prepared to explain and justify it to the examiners. Typical questions might be “explain your research question and how you derived it.”
3. Coverage of the literature
The examiners will want to be sure that you understand the literature which underpins your work. An important criterion for the award of PhD in that the candidate demonstrates knowledge of the relevant work of other researchers in your field. So it is likely that they will ask some questions which test your knowledge of the academic literature within your subject. You may, for example be asked: “Which are the three most important papers which relate to your thesis?”, “Whose work has most influenced yours, and why?”, or “Whose work is the closest to yours?” and “How is your work different to theirs?”
Prepare for your viva. One question at a time.
Prepare answers to the most common PhD viva questions with this interactive template. It’s free to download and it’s yours to keep forever.
4. Methodological questions
The methodology, and the approach you have taken, is another area that the examiners are likely to want to discuss. This could come in the form of a question asking you to justify your approach: “Why did you choose to use a qualitative approach?” and “What alternative approaches might you have chosen?” or more detailed questions about the methods used: “Why did you use focus groups rather than interviews?” or “How did you select the group of people to interview?”
Most PhD’s have some ethical issues which they need to be considered. This may take the form of a specific question such as: “Explain the ethical protocols and approval procedures which you followed” or “Did you obtain informed consent?”, or a more general question, such as: “What are the ethical implications of your work?”.
6. Decisions you made
Along the way, you will have had to take several decisions as to the next step to take. The examiners may ask you to discuss and justify these. This could take the form of a very general question: “What was the most important decision that you had to make during the course of your PhD?”; “Which decisions would you change if you were to do the work again?” or something much more specific: “Why did you choose to test your system on this group of people?”
7. Evaluation
It is always important to show that you have evaluated the work that you have done. Typical questions could be: “How did you set about evaluating the work you did?”, “How does your work compare to that of others?”, “What is the strongest point of your work?”, “Which part of your thesis are you most proud of, and why?”, and “Which is the weakest part of your work?”.
8. Future Work
Examiners will almost always ask about possible areas for future work. Questions could be: “If you had another year, what would you do?” or “How would you continue with the work? What are the next steps?”
Wrapping up
With the right preparation and mindset, the viva is nothing to be scared of. Work through model answers to the questions above, have a good read of your thesis, and have faith that you know your research better than anyone else. Then, on the day, try to have fun.
If you want to be as prepared as possible for your viva, book yourself onto a one-on-one mock viva with Professor Smith. Boost your confidence with a full practice run before the big day. Click here to find out more.
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This article has been incredibly helpful in preparing a plan and script for my upcoming viva. It introduced me to several intriguing questions I hadn’t considered before. The real test will be how well the viva goes, but at least I now have a head start. Many thanks!
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Viva Questions
- Updated on
- Nov 22, 2024
What are viva questions? A viva simply means a university examination during which students answer questions in speech and these questions are commonly based on a particular project or discipline. Viva questions are an important part of an academic program and often take place at the conclusion of a semester/year. Although viva questions can vary, they commonly focus on four aspects: “What the project is about?”, “What were the key findings or observations?”, “What was the process?” and “Why do the observations matter?”. However, in some cases, these questions can be more diverse. If you want to know how to tackle these PhD viva questions properly, then this blog is a must-read for you!
This Blog Includes:
1. summarize your project/thesis/research in 3 minutes, 2. what is the strength and weakness of your research, 3. what makes your thesis work original, 4. elaborate on how your findings relate to literature in your field, 5. tell me about yourself, 6. summarise your key findings, 7. highlight the strong and weak areas of your research, 8. what were the major motivations behind this research, 9. elucidate the process of evaluation, 10. what is the key focus of this research, 50 common viva questions, 25 phd viva questions, viva questions on research methodologies, analysis and research findings: viva questions, viva questions for physics, viva questions for chemistry, viva questions for biology, viva questions for higher education, tips and tricks to ace the viva, 10 most important viva questions with answers.
Whether you are a PhD or a school student, viva exams are equally tough for everyone. But don’t worry, we have a solution to calm you down! Here are 5 commonly asked questions with answers:
To answer this question correctly, you need to be well-versed in the entire project. Start with an answer by explaining why did you select the topic of your project/thesis/research and close your explanation by providing an optimum solution to the problem.
Carefully analyze the strength and weaknesses of your research and while answering, make sure you talk about your weaknesses also and not only your strengths.
While answering, keep in mind what was known before and what you have added as part of being awarded your PhD is to contribute novel knowledge.
Explain how your findings connect with the literature review of your project and what its contributions are in terms of the field of your research. Does it further expand the literature? Does it highlight some new observations? Does it add to the literature in this field? Answer these main questions.
Talk about yourself and your areas of interest. Focus on the areas you are extremely positive about. Talk about your past achievements and what brings you to this position. Keep it professional.
Must Read: How to Ace “Tell Me About Yourself” in College Interview?
For this common viva question, focus on what you observed and found through your research project, how it connects with your hypothesis as well as what concluded through this research.
Mention the strengths first and elaborate on how they connect with the key findings. Then, you can underline the weak areas and the factors that could have been transformed into strengths.
Focus on what inspired you to carry out this research, and cite certain instances which helped you select this topic as well as the field for your project.
Elaborate on how you evaluated the key findings in your research, the key factors involved, whether the evaluation process faced some obstacles, how it could have been better and what was the reason you choose a particular process of evaluation.
While answering this, keep a summarised version of your research in your mind and then talk about the area of the primary focus of research. In order to demonstrate that your research is viable, it is essential to identify some of the key questions that it addresses.
Mostly research-based viva questions are asked in the case of a doctoral thesis wherein the key aspect of the process is to identify the thought behind the development of the specific paper. It is done to determine the knowledge and originality of the researcher and to assess their further interest in the field.
Below are some of the most common viva questions.
- Tell me about yourself.
- Summarise your research/thesis in 3 minutes.
- Tell us how your research contributes to knowledge discourse.
- What are the practical applications of your research?
- What is the strength and weakness of your research?
- How does your research help solve the underlying problems?
- Can you explain your thesis in a sentence?
- How did you come up with the subject of your research/thesis?
- What was the source of inspiration behind this thesis/research?
- What is the key idea that is unexpendable to your thesis?
- What contributions are you looking forward to making in this area of study?
- What is the key focus of this research?
- Where can we locate the originality in your paper?
- What are the core areas of debate in this paper?
- What research methodology have you applied to address this issue?
- What were the alternative methods you could have used to address the subject matter of concern?
- Why did you feel it necessary to spend your resources in this area of study?
- What aids did you use to support your research?
- Which pertinent research papers did you use in your research?
- Can you name 3 remarkable research papers in this stream?
- Explain the recent developments in this field.
- How did you come up with these questions you have discussed in your paper?
- Describe the necessary decisions taken in your process.
- Elucidate the process of evaluation.
- Ponder over the strong and weak aspects of your research.
- What is the relevance of your research in the current scenario?
- Where do you think your research can be practically applied?
- Which aspects of your research are you looking forward to being published?
- Give us some insights into the references in your thesis.
- What have you achieved in the process of this PhD?
- Elaborate on how your findings relate to literature in your field.
- Highlight the strong and weak areas of your research.
- What were the major motivations behind this research?
- How would you propose future research as a follow-up to this project?
- Who will be more interested in this research project?
- How is your research project relevant to your fellow researchers?
- What was the process behind the research questions you selected?
- Name some alternatives to your chosen research methodology.
- Which of your research observations are you most interested in/curious about?
- Name some prominent achievements of your research.
A PhD viva is a final examination in which a candidate answers questions from an academic panel on their work and understanding of their chosen subject area. This is often used to determine whether the candidate has effectively proved that they have learned enough about their specialised study topic to produce original work.
During a PhD viva, the questions are frequently based on the original study proposal and any other written material that has already been provided. Read the top 25 PhD viva questions below:
- What is the area in which you wish to be examined?
- What have you done that merits a PhD?
- Summarise your key findings.
- What’s original about your work?
- Which topics overlap with your area?
- Where do current technologies fail such that you (could) make a contribution?
- Who are your closest competitors?
- Can you summarise your project in 2 lines?
- How can this research help other students working in the same field?
- Which of your findings is your personal favourite?
- Is your research inspired by some incident in your life?
- Why did you choose this method to conduct this research?
- What motivated you to conduct this research?
- What was the biggest challenge that came your way?
- What were the alternatives to this methodology?
- How would you evaluate your work?
- Were you short of any resources while conducting this research?
- Can you tell me about the strongest point of your research?
- What is the weakest point of your research?
- . How did you deal with the ethical implications of your work?
- What original contribution has your thesis made to this field of study?
- Whose work has most influenced yours?
- What ethical considerations did you apply?
- Did your study go as expected? If you had to start the thesis again, what would you do differently?
- Now that you’ve completed your study, what did you enjoy about the process?
Preparing for an interview for the Statistician or Survey Specialist role? Then worry not! Here are the most important viva questions on research methodologies:
- Under which circumstances are quantitative as well as qualitative research methods fruitful?
- Could you distinguish between case-based and observational-based research methods in a few words?
- What is a scientific study and what are its essential features?
- You must have faced some ethical issues while conducting research. How did you handle it?
- What method did you use to collect data?
- Was there any other way in which you could have assimilated the data? If yes, then how?
- What are the main achievements of your research?
- What advice would you give to a research student entering this area?
- What is the relevance of your work to other researchers?
- How did your research questions emerge?
Also Read: Research Institutes in India
When it comes to a career in Research, the outputs which you obtain are assessed on multiple factors. Enlisted are some viva questions which will help you prepare in advance:
- How would you summarise your findings in a few words?
- You have used 3 different techniques to analyse the final results. Could you elaborate on all of them?
- Was there any chance of implementing a different type of analysis technique?
- Apart from the topic, you selected, in what other applications can your research findings be used?
- Out of the given results, which of the findings, according to you, can be beneficial in the near future?
- Is the problem you have tackled worth tackling?
- What would you have gained by using another approach?
- Which are the three most important papers that relate to your thesis?
- What would have improved your work?
- What are the main issues and debates in this subject area?
- What motivated and inspired you to carry out this research?
- How did you come up with the idea for your project?
- How did you establish the limits of your data collection? How did you analyze the data?
- Is your work original? What is novel about your work?
- What are the contributions of your thesis to knowledge?
- What is the future of your research area? How does your work relate to other topics in your area?
- Can you give an overview of your thesis?
- Can you answer questions about your introduction?
Subjective Questions for School
Be it for Chemistry or Biology practicals , from 10th standard onwards, students have to appear for vivas. The concerned viva questions pertain to the subject that the students have studied in the course of the entire year. The viva that one appears for at the senior secondary level is based on the experiments that the students perform to test their understanding of the research. Apart from those experiments, the students are also asked several questions to estimate their practical understanding of the key areas of study.
Viva questions for Physics are mainly based on concepts and topics from Physics textbooks. Here are the most common viva questions for Physics Class 11 and Class 12:
Viva Questions for Class 12 Physics
- What is Ohm’s Law?
- What do you mean by ‘interference’?
- Define tangent law.
- Name the type of motion shown by the Torsional pendulum.
- What happens with resonance in the LCR circuit?
- What do you understand by the order of the spectrum?
- How is Wedge Film Experiment useful?
- Define parallax and how it is removed.
- How does the emission of light is carried out by LED?
Also Read: Physics Project for Class 12: Top 50 Ideas & Experiments
Viva Questions for Class 11 Physics
- Name the units of the vernier scale.
- What do you understand by Zero Error (Z.E)?
- What are the two parts of the Screw Gauge?
- Name one mechanical advantage of a Screw Gauge.
- What is Focal Length?
- What are the factors that impact surface tension?
- Define the time period of a bar.
- What is Simple Harmonic Motion (SHM)?
Viva questions for Chemistry are mainly based on concepts and topics from Chemistry textbooks. Here are the most common viva questions for Chemistry Class 11 and Class 12:
Viva Questions for Class 12 Chemistry
- What is Valency?
- What is the value of Avogadro’s number?
- What is the monomer of Polyethylene?
- What are polymers?
- What is the IUPAC Name?
- Differentiate between addition and condensation polymer
- What is the oxidation and reduction reaction in the electrolytic process?
- What is Titration?
Also Read: Chemistry Project for Class 12: Topics & Sample Projects
Viva Questions for Class 11 Chemistry
- Define the term ‘crystallisation’
- What is solubility?
- Why is crystallization done?
- What is Kipp’s waste?
- What is a Saturated Solution?
PhD viva questions for Biology are mainly based on concepts and topics from Biology textbooks. Here are the most common viva questions for Biology Class 11 and Class 12:
Viva Questions for Class 12 Biology
- What is litter?
- What is the shape of a pollen grain
- What is tectum?
- What are pollutants
- What is hummus
- Define Mitosis
- Why is Mitosis called Somatic Cell Division
Also Read: How to Ace Class 12th Biology Practical?
Viva Questions for Class 11 Biology
- How many types of proteins are there
- What are enzymes
- What is nucleic acid?
- Examples of high-protein food
- Full form of DNA
- Full form of RNA
- What are Mendelian Laws
- What is placentation?
- What are monadelphous and diadelphous stamens?
- What is the flower’s importance to the plant?
- To which family china rose belongs?
Admission tutors at the postgraduate level conduct viva or interviews to establish whether graduates are committed to and prepared for studying the master’s or PhD level courses. These are less formal than a job interview , but you still need to take them seriously – your aspirations to pursue overseas education could depend on your performance.
Let’s say you come from a Mass Communication background and you’ve made a documentary on “ underprivileged sections of society” . Then you might be asked about the process of the development of the movie, how long did it take to gauge the key aspects of the film or the perspective behind the direction process.
Though the research you do in your PhD is a massive achievement, you need to be prepared for the exhaustive viva session with the experts. The PhD viva questions are a chance for students to discuss their work with professionals. Its formal purpose is to ensure that the student understands and can explain their thesis. It involves lots of stinging questions and conceptually complex debates. How can PhD scholars best prepare themselves? Let us take a look at the different tips for getting through your viva questions:
- Calm down and breathe
- Believe in yourself
- Do something fun
- Go in with a good attitude
- Look presentable
- Read your thesis
- Know the rules
- Make a list of your own corrections
- Make plans to celebrate
- Try to enjoy it
Must Read: How to Crack an Interview [20 Scientifically Proven Tips]
Related Reads:-
Ans. These are some of the basic viva questions: Tell me about yourself. Summarise your research/thesis in 3 minutes. Tell us how your research contributes to knowledge discourse. What are the practical applications of your research? What is the strength and weakness of your research?
Ans. Every institution is different; some have only two examiners, while others include a convenor as well. Some institutions may require you to prepare a talk to present before the viva (this was the situation for me, and it was excellent preparation for the exam).
Ans. The examiners will frequently begin a viva with an introductory question, such as “Spend five or ten minutes telling us about your work, what you have done, and what contribution you have made” or “Summarise your work for us in a single sentence.” These are some of the first PhD viva questions that you can encounter.
Preparing for the viva questions beforehand helps you confidently answer them in front of the panel of experts who not only test your subjective knowledge but also do grading on the basis of your level of confidence.
If you are looking for admission to a university abroad and want to impress the admission committee, Leverage Edu experts can provide you with tips and tricks to ace the interview. Call us immediately at 1800 57 2000 for a free 30-minute counselling session.
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what should be an ideal answer for the question “tell me about yourself?”
There is no ideal answer to the question ‘Tell me about yourself’, as it is very subjective and depends on your career trajectory. But the best way you can answer it is by covering the following points:
1. Share your background 2. Tell them about your education 3. Share any volunteer, internship or work experience you have 4 You can also tell them about your hobbies
It is advisable that you share your experience chronologically so it does not get confusing for the interviewer.
For any study abroad-related query, please get in touch with our experts through this number: 1800572000 or drop us a mail at [email protected] .
Thanks Team Leverage Edu
Thank you for this helpful information… Its really good and givea confident to me …
Hi, Venkatesh! Thanks for your comment. We are referring you few blogs to explore: Profit and Loss Formula Questions Types of Reasoning Questions in Competitive Exams Interview Questions and Answers
Most useful information for a researcher. Thanks a lot for guiding several research students.
Hello! Glad that you found the blog informative.
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Experiences of a London PhD student and beyond
Common PhD Viva Questions
It can be pretty difficult knowing how to prepare for your PhD viva. Having successfully defended my own STEM PhD remotely in the last year, I want to help you to prepare! What follows are some common PhD viva questions which your examiners may ask you. Plus some additional advice based off my own PhD viva experience.
For an intro to the PhD viva including the typical structure and potential outcomes please see my introductory post:
- How to Defend a Thesis: An Introduction to the PhD Viva
How Much Do You Need to Prepare For A PhD Viva?
There is no hard and fast rule for how much you need to prepare. And unlike a written exam, there are of course no past-papers to practice on!
It may help ease your mind to think about what the purpose of a PhD viva is. Namely the purpose of the PhD viva (or defence) is to check that:
- You did the work;
- You understand the work;
- The research is up to the standard for a PhD.
For more detail see my separate post here including Imperial’s PhD viva mark scheme.
In hindsight I probably didn’t spend as much time preparing for my viva as is normal. Though I did unexpectedly move house less than a week before !
Besides reading through my thesis once in the few days leading up to it, I didn’t spend much time thinking up answers to questions or “revising” certain topics which could come up. The viva went fine, but it wouldn’t have done me any harm to have been a little better prepared.
It certainly helped that I’d managed to schedule a viva which took place less than six weeks after I submitted the thesis so it was all very fresh in my mind. If you submitted your thesis months before your viva I’d suggest spending slightly more time refreshing your memory in preparation for questions you may get asked.
In summary, I think it’s useful for all PhD students to get an idea of some potential lines of questioning for their oral exam!
Update: Keen to get prepared for your viva? I’ve put together a set of viva preparation worksheets which are available in the resource library. Click the image below for free access!
Listed below are common PhD viva questions which I’ve roughly grouped together. We’ll start with some higher-level questions about your PhD which should be quite easy and friendly, then progress through to some more technical (and potentially unfriendly!) questions.
It is worth noting that many examiners will ask for a short presentation at the start of the viva and this could eliminate some potential questions. In this list I’ve left in the main questions I’d expect for this presentation to address, such as what future work you’d recommend.
Very few of the questions are ones you’re guaranteed to get asked, but I can assure you that you’ll get asked at least some of them!
General PhD Viva Questions – usually friendly!
These ones are simply inquisitive and you don’t really have to worry about getting caught out. The examiners are simply interested in the work and want an insight from someone who has spent the last few years working on it.
- What is the most important finding from your PhD work?
- What was the motivation behind this research?
- Who is your research relevant to?
- Which aspects of your work are you publishing? Follow on: and where?
- What future work would you recommend?
- What are the limitations of your research?
- Which aspect of your work surprised you the most?
- What are the potential applications of your PhD research?
Method-Specific Questions – mostly friendly!
These questions dive a little deeper but even so shouldn’t be too much of a cause for concern. They come down to your own judgement and as long as you justify your decicisions you’ll be fine in answering them.
- Why did you do [things] a certain way?
- What were the alternatives to [this certain method]?
- Why did you test [that specific number] of samples?
- What effect did you think changing [something in your method] would have?
- What do you think you could have gained by using [another approach]?
- Why did you not use [another technique]?
- How did you deal with the ethical implications of your work?
Results & Analysis-Specific Questions – mostly friendly!
In a similar manner to the previous section about your methodology, you’ll often get some questions targeting your analysis and presentation of results.
- What is this graphical figure illustrating?
- Why was [this analytical technique] appropriate? Follow on: why did you use [this other technique]?
- Which of your results do you find the most interesting?
- How do you know that your findings are correct?
Literature Questions – may be less friendly!
This is where things may get tough if your examiners want to try and test your limits. Even so, they’ll still likely cut you some slack. If you have 100+ references it’s very possible that under the nerves of your exam you can’t remember specifics for each and every reference. Just don’t make things up. They’d rather you were honest than trying to deceive them.
- Please explain the key findings of reference number [X]
- Which papers would you say had the biggest impact on your work?
- What do you think are the biggest differences between [these two previous studies]?
- What have been the biggest advancements in the field over the last 10 years?
- Why did you not reference [this other study]?
- How does your work compliment the existing literature?
- What do you think the next big advancements will be in the field?
Highly Technical Questions – potentially very unfriendly!
These are the ones I was a bit scared of getting, but it is a PhD viva after all. Of course it should be expected that you have a solid understanding of the principles that underpin your project. Even so it can be unnerving thinking of how large the range of potential questions like this can be!
Unlike at a conference or in other settings where you may be able to brush over things you’re not 100% comfortable with, there is no hiding when your examiners need to test your knowledge. Particularly when they have hours of time at their disposal to do so!
- Explain how [a technique] works. This could be anything from sample preparation, equipment and analysis through to statistics. I’ve known people to get asked to explain things like a statistical t-test from first principles, with follow-on questions being asked with every answer to drill deeper.
- Explain [some fundamental concept, phenomenon or principle]. Just like the last question but applied to basic-sciences. I’ve known students to get asked questions such as: explain energy (to a mechanical engineer) and explain toughness (to a materials scientist). I’m sure we can all explain these concepts to a certain level but my concern was whether or not I could explain them at a deep enough level to satisfy the examiner.
With both of these types of questions there ultimately comes a point where you (or the internal examiner ) can push back and say that answering that question was not the focus of your PhD!
What Questions I Got Asked at My Own PhD Viva
I was really surprised at my own viva how few questions I actually got in general.
The viva lasted a whopping five hours (excluding a quick break) and yet almost all of the time was spent discussing improvements to my viva to help with publishing papers.
Even so, I could have done with putting a bit more time into preparing for potential questions: which was my motivation to help you by putting together this post!
The few questions I had included:
- If you were to do the project again would you do anything differently?
- Clarification of what I meant by certain sentences in my thesis .
You may be wondering if I avoided getting asked deeper questions by the examiners because I already had a relationship with them so they were satisfied with my knowledge and capabilities. But I didn’t really know the examiners! I’d met my external examiner at a conference and he had seen me present but I’d never actually met my internal examiner before.
Instead, what I think did go a long way to helping was having already had something published in a respected journal.
Nevertheless, in a way I actually walked away a little unsatisfied by the lack of questioning at my PhD viva.
It was great to get so much feedback on my thesis which has already helped to get two more papers published since the viva, but I felt like it would have been nice to feel a bit more taxed and known that I could hold my own in the exam if it came down to it.
Now looking back on the viva 10 months later, I’m just happy to have the PhD done!
My Tips for Answering Common PhD Viva Questions
- Keep calm and take your time before answering . There is no rush to answer questions. Having a sip of a drink may help provide a pause for thinking up an answer.
- Tell the truth. If you don’t know something, just say so! It’s likely the examiners will quickly be able to tell that you don’t know what you’re talking about. Plus, there is the risk that they’ll ask deeper follow-on questions which could unravel any lies.
- Try to enjoy the experience. Think of it as a discussion, rather than a police investigation. Your examiners are interested in the work and want to hear more about it!
If you’d like personalised help with preparing for your PhD viva I am now starting to offer a small number of one-to-one sessions. Please contact me to find out more or click here to book a call.
I hope these common PhD viva questions can help you to prepare for your own viva.
If there are other aspects of the examination you want covered, just let me know.
I have many more upcoming PhD (and beyond!) posts . I f you want to get notified about them you can subscribe here:
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100 Machine Learning PhD viva Questions
100 machine learning phd viva questions: a comprehensive guide for defending your thesis.
Are you preparing for your Machine Learning PhD viva and feeling overwhelmed by the thought of the questions you might be asked? You’re not alone. The viva, or oral examination, is a crucial part of the PhD process, and it can be challenging to know how to prepare for it.
Fortunately, we’ve got you covered. In this article, we’ve compiled a list of 100 Machine Learning PhD viva questions that are likely to come up during your examination. By reviewing these questions and preparing thoughtful answers, you can boost your confidence and improve your chances of success.
- What is your research topic, and what motivated you to pursue it?
- What are the key research questions you aimed to answer in your PhD project?
- What is the main contribution of your research to the field of Machine Learning?
- Can you explain the technical approach you used to tackle your research problem?
- What are the limitations of your research, and how did you address them?
- What are the potential applications of your research in industry or academia?
- How does your work fit into the broader context of the Machine Learning field?
- What were the key challenges you faced during your research, and how did you overcome them?
- Can you explain the methodology you used to collect and analyze your data?
- What are the key insights you gained from your research , and how do they contribute to the field?
- What are the main strengths and weaknesses of the Machine Learning methods you used in your research?
- Can you explain the differences between supervised and unsupervised learning, and when to use each method?
- What are the key steps in building a successful Machine Learning model?
- What are the advantages and disadvantages of using deep learning models?
- How do you handle overfitting in your models, and what techniques do you use to prevent it?
- What is regularization, and how does it help prevent overfitting?
- How do you handle missing data in your Machine Learning models?
- What is cross-validation, and how does it help evaluate the performance of your models?
- Can you explain the difference between precision and recall, and why they are important metrics in Machine Learning?
- What is the curse of dimensionality, and how does it affect the performance of Machine Learning models?
- Can you explain the difference between a generative and a discriminative model?
- What are the advantages and disadvantages of using decision trees for Machine Learning?
- Can you explain the difference between gradient descent and stochastic gradient descent?
- What is backpropagation, and how does it work in training neural networks?
- What are convolutional neural networks, and how are they used in computer vision?
- Can you explain the difference between a convolutional layer and a pooling layer in a CNN?
- What are recurrent neural networks, and how are they used in natural language processing?
- Can you explain the difference between a LSTM and a GRU?
- What are autoencoders, and how are they used in unsupervised learning?
- What is transfer learning, and how can it be used to improve the performance of Machine Learning models?
- What are adversarial attacks, and how do they affect the robustness of Machine Learning models?
- What is reinforcement learning, and how does it differ from supervised and unsupervised learning?
- Can you explain the difference between on-policy and off-policy learning in reinforcement learning?
- What is Q-learning, and how does it work in reinforcement learning?
- What are the challenges in scaling Machine Learning models, and how can they be addressed?
- How do you evaluate the performance of a Machine Learning model, and what metrics do you use?
- Can you explain the difference between accuracy and F1 score, and when to use each metric?
- How do you interpret the results of a confusion matrix, and what insights can you gain from it?
- What are the different techniques for feature selection, and how do you decide which one to use?
- Can you explain the difference between feature extraction and feature selection, and when to use each technique?
- What are the different types of clustering algorithms, and how do they differ from each other?
- Can you explain the difference between K-means clustering and hierarchical clustering?
- What are the challenges in clustering high-dimensional data, and how can they be addressed?
- What are the different types of classification algorithms, and how do they differ from each other?
- Can you explain the difference between logistic regression and support vector machines?
- What are the different types of ensemble learning methods, and how do they work?
- Can you explain the difference between bagging and boosting?
- What are the advantages and disadvantages of using random forests for classification tasks?
- What are the different types of time-series forecasting models, and how do they differ from each other?
- Can you explain the difference between ARIMA and exponential smoothing models?
- What are the different types of anomaly detection algorithms, and how do they work?
- Can you explain the difference between unsupervised and semi-supervised anomaly detection?
- What are the different types of deep learning architectures, and how do they differ from each other?
- Can you explain the difference between a feedforward neural network and a convolutional neural network?
- What are the different types of optimization algorithms, and how do they differ from each other?
- Can you explain the difference between batch gradient descent and mini-batch gradient descent?
- What are the different regularization techniques, and how do they prevent overfitting?
- Can you explain the difference between L1 and L2 regularization?
- What are the different types of data augmentation techniques, and how do they improve the performance of Machine Learning models?
- Can you explain the difference between data augmentation and transfer learning?
- What are the different types of hyperparameter tuning techniques, and how do they help optimize Machine Learning models?
- Can you explain the difference between grid search and random search?
- What are the different types of model interpretability techniques, and how do they help understand the inner workings of Machine Learning models?
- Can you explain the difference between LIME and SHAP?
- What are the ethical considerations in Machine Learning, and how do you ensure that your research is ethically sound?
- Can you explain the difference between bias and variance in Machine Learning, and how do you balance them?
- What are the challenges in building Machine Learning models for real-world applications, and how do you address them?
- Can you explain the difference between batch learning and online learning, and when to use each method?
- What are the different types of data preprocessing techniques, and how do they prepare data for Machine Learning?
- Can you explain the difference between normalization and standardization?
- What are the different types of distance metrics, and how do they measure similarity between data points?
- What are the different types of optimization problems in Machine Learning, and how do you solve them?
- Can you explain the difference between convex and non-convex optimization problems?
- What are the different types of regularization techniques, and how do they prevent overfitting?
- Can you explain the difference between dropout and weight decay regularization?
- What are the different types of learning rate schedules, and how do they impact the training of Machine Learning models?
- Can you explain the difference between a fixed learning rate and an adaptive learning rate?
- What are the different types of data imbalance, and how do you handle them in Machine Learning?
- Can you explain the difference between oversampling and undersampling?
- What are the different types of neural network architectures for sequence modeling, and how do they differ from each other?
- Can you explain the difference between a Recurrent Neural Network and a Transformer?
- What are the different types of attention mechanisms, and how do they improve the performance of Machine Learning models?
- What are the challenges in building Machine Learning models for natural language processing, and how do you address them?
- Can you explain the difference between word embeddings and character embeddings?
- What are the different types of text classification algorithms, and how do they differ from each other?
- What are the different types of named entity recognition algorithms, and how do they work?
- What are the different types of sentiment analysis algorithms, and how do they determine the sentiment of a piece of text?
- What are the different types of topic modeling algorithms, and how do they discover topics in a corpus of text?
- What are the different types of Machine Learning models for image classification, and how do they differ from each other?
- Can you explain the difference between a Convolutional Neural Network and a Residual Neural Network?
- What are the different types of object detection algorithms, and how do they detect objects in an image?
- What are the different types of image segmentation algorithms, and how do they segment an image into regions?
- What are the different types of generative models, and how do they generate new data samples?
- Can you explain the difference between a Generative Adversarial Network and a Variational Autoencoder?
- What are the different types of Machine Learning models for speech recognition, and how do they differ from each other?
- Can you explain the difference between a Hidden Markov Model and a Deep Neural Network for speech recognition?
- What are the different types of Machine Learning models for time-series forecasting, and how do they differ from each other?
- Can you explain the difference between a recurrent neural network and a convolutional neural network for time-series forecasting?
- What are the different types of Machine Learning models for recommender systems, and how do they recommend items to users?
- Can you explain the difference between collaborative filtering and content-based filtering for recommender systems?
These 100 Machine Learning PhD viva questions cover a wide range of topics and concepts in Machine Learning, from basic concepts such as linear regression and decision trees, to more advanced topics such as deep learning, natural language processing, and image recognition.
By preparing for these questions, you will be well-equipped to defend your thesis and demonstrate your knowledge and expertise in the field of Machine Learning. Remember to keep practicing and honing your skills, as the field of Machine Learning is constantly evolving and there is always something new to learn. Good luck with your viva!
Also Read: Top 50 Possible PhD Viva Questions
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- decision trees
- Deep Learning
- graduate school
- image recognition
- linear regression
- Machine Learning
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- neural networks
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Types of PhD Viva Questions. Generally, examiners prepare a series of questions for you to answer at the PhD viva voce examination. These questions are primarily based on your thesis. However, the questions asked in PhD viva examinations can be broadly grouped under four basic headings: General Questions; Research Context and Methods; Analysis ...
Computer Science CS710 Nasty PhD Viva Questions (Extract) ... The PhD viva is an open-book exam: you can bring any materials you want. Here is what I think one should bring to the viva: ... Here are some generic viva-questions - you should instantiate each question for your particular thesis, and have a framework for answering it worked out ...
The PhD viva is an oral examination conducted by a panel that takes place as part of the PhD defence. The panel asks a PhD student questions about their research project and thesis, which requires the candidate to demonstrate knowledge in the subject area and understanding of how it applies to their project's topic.
Saying "I do not know" to this question can result in a Phd failure. ... (2-3 months ago) passed my PhD viva in Computer Science at a UK institution in the top 100. I will relay the useful points from my viva experience, but I preface this by saying that yours may differ. Ultimately the viva is a product of the examiners, and different ...
2. The aims, objectives, research questions, and hypotheses In your thesis you will have set out the purpose of your work. Depending on the discipline that you working in, you may have called this an aim (with accompanying objectives), a question (or a series of questions) or an hypothesis (or a series of hypotheses).
25 PhD Viva Questions A PhD viva is a final examination in which a candidate answers questions from an academic panel on their work and understanding of their chosen subject area. This is often used to determine whether the candidate has effectively proved that they have learned enough about their specialised study topic to produce original work.
the format a viva can take. A mock viva can be a good opportunity to practice answering the questions and engaging in discussion rather than just preparing on paper. Practise with others You can also ask other colleagues (staff or PhD students) you may know or have worked with to read your thesis (or parts of it).
What follows are some common PhD viva questions which your examiners may ask you. Plus some additional advice based off my own PhD viva experience. For an intro to the PhD viva including the typical structure and potential outcomes please see my introductory post: How to Defend a Thesis: An Introduction to the PhD Viva
This paper presents questions within a consideration of the nature of doctoral viva examinations from an international viewpoint. We argue that preparation for the viva should begin early ...
Preparing for a Machine Learning PhD viva? This comprehensive guide features 100 questions covering a wide range of topics, from basic concepts to advanced topics like deep learning, NLP, and image recognition. Be well-equipped to defend your thesis with this guide.