The Best PhDs to Get: Elite PhDs That Open Doors to Success!

In this video I share with you the best PhD is to get.
▼ ▽ Sign up for my FREE newsletter
Join 19,000+ email subscribers receiving the free tools and academic tips directly from me:
andrewstapleton.com.au/newsle...
▶ Become a Master Academic Writer With AI using my course: academy.academiainsider.com/c...
▶ Use my Ultimate PhD Kickstart: 12 Point Success System for Aspiring PhDs to start your PhD strong: academy.academiainsider.com/c...
▶ My best KZbin advice curated into an an easy to follow course, Effortless Academia: academy.academiainsider.com/c...
▶ Applying for a PhD? Get my FREE PhD application resource pack to apply with confidence: www.subscribepage.com/freeapp...
▶ Learn what I wish I had known before starting my PhD in my ebook bundle: academiainsider.com/ebook-bun...
................................................
▼ ▽ TIMESTAMPS
0:00 - introduction
0:43 - Option one
2:34 - Option two
4:50 - Option three
6:18 - Option four
7:44 - Option five
9:53 - Wrapping up
................................................
▼ ▽ RECOMMENDED TOOLS AND SERVICES
▶ Best dissertation editing service - www.beyondphdcoaching.com/dis...
▶ Best PhD Writing Tool - Writefull - link.andrewstapleton.com.au/w... (Get 10% off with my link)
▶ Best Literature Search - Litmaps - app.litmaps.co (Get 10% off with code STAPLETON)
▶ Need PhD advice? - Beyond PhD Coaching - www.beyondphdcoaching.com/sta...

[@iminsaf7833]

1. AI 2. Cybersecurity 3. Maths education 4. Engineering 5. Government priority area

[@akuwardmoments]

I studied engineering for my BS and MS, and I'm doing a chemistry PhD. In my opinion, studying engineering first and then a natural science was a very effective move, and you could absolutely go the opposite way as well. Engineering is a field that teaches you to work hard, while natural sciences teach you how to think hard. The gap between the two is closing anyways. It took 100 years to apply the discovery of electricity into machines that played any part in human society. Then, it took a few decades to apply quantum mechanics into publicly available devices. The gap between discovery and widespread application is closing quickly, and I think studying both the fundamental sciences and the optimal applications of engineering will enable you to facilitate the closing of that gap across the board.

[@kevinmarrs3372]

I did the opposite. BSc and MS in Chem. Now I’m doing Chem Eng PhD

[@AlviondeAlba]

I do a similar approach. Did my BS and MS in engineering, BS in dental materials and MS in polymers and composites. Started working with surface functionalisation company afterwards. Used the knowledge of modification treatments to now do a PhD in Medicine (even if i think of my topic more as Biomedical engineering). See where this will take me to :). But in my opinion the engineering side contributes greatly to my PhD, so that its not just fundamental research but more applied research with a more industry focused approach. Hopefully setting me up for my goal to transition to anything within medical material engineering in industry afterwards.

[@gorluxor]

I am watching the video while in the office for my AI Ph.D. and enjoying the content. Keep up the excellent content @Andy

[@takiyaazrin7562]

Great analysis!

[@meghaemerse2700]

Hi Andy, thank you for all the videos which you are creating related to PhD and researches. Its so useful. I have request. Can you please do a video on tips for preparing for an interview after PhD or for a Postdoc position? Please. Thanks

[@robensonlarokulu4963]

Usually, reputable industry jobs (not software development) for machine learning/AI positions ask PhD holders to have high-quality papers at top-tier places. You can not get top-tier papers with "a" PhD. Usually, "'the'' PhD that satisfies these conditions come from top labs at elite institutions.

[@JAlexanderCurtis]

I’m getting a PhD right now and using AI to find cybersecurity attacks. So I guess I’m all good and have nothing to worry about.

[@gilbertofrancisco1182]

Amazing video.👌👌

[@ethanbarlow1804]

Starting my PhD in Robotics this fall! I'm so excited for the growth in this field.😁

[@BatistaDiscovery]

I am mechanic engineer and I hope start my PhD in robotic soon 😊

[@andreasa1293]

Best of luck future Dr. Ethan Barlow!

[@m.ehtizan]

Hey Andy, I just watched your video and I must say that it was really informative and well-made. I was wondering if I could help you edit your videos and also make highly engaging shorts for you.

[@masteryourstudies]

Those fields are all great to pursue a PhD. A big problem I see with this range is that society needs social scientists and humanities PhDs to work with all those STEM PhDs. So a good tip for those interested in social sciences and humanities would be to do a PhD that complements those fields such as AI-ethics, Cyber-privacy and the like. Having bright minds in STEM is great but they are often not exposed to critical or ethical thinking, which one will develop in a humanities program.

[@aperkins07]

Disagree on it being a problem nor are they needed as much. Math PhD is heavily underrated and can contribute more than any of those humanities programs as it's more versatile. Tech can support those programs, but I'm willing to bet there's such a big pay gap between tech and social sciences that it'd give very little to no incentive for ppl who have tech skills to apply them in social sciences vs tech industry so social sciences will have to wait probably a long while before those skills become more and more common place to get any value out of it in that field. Ethics is probably the biggest issue concerning tech, but in order to discuss ethics regarding tech, one should have a full understanding of implications or impacts from tech and a humanities PhD more than likely isn't going to be able to have an edge on that against a tech PhD. I've honestly never met a humanities PhD have more critical thinking skills than a math PhD though probably met one exceptional economist who could stand toe to toe with them in that regard

[@ruicarrilho5721]

The idea that a STEM PhD would have less critical thinking than a humanities one is hilarious to me. And wrong, of course

[@masteryourstudies]

@@ruicarrilho5721 i'm not talking about the ability but the contents of the PhD program

[@johnadams-kf3my]

@@ruicarrilho5721 This comment kinda proves his point...

[@aperkins07]

@@johnadams-kf3my not really. His comment went against the original commenter's statement that STEM phds are not exposed to critical thinking

[@Eta_Carinae__]

Andy, or anyone else here for that matter, I'm interested in getting into Quantitative Life Sciences. It's got a bit of everything that I'm interested in - AI, Statistical Physics, Universal Biology, etc. I'm wondering: what would you do as far as education is concerned to obtain a career in QLS? It's a bit difficult to find a clear path on account of there really being no degree or industry specific roles, even though the field is well-implemented in both. Cheers.

[@GigaNormie]

Engineering is a general topic. You have to be more specific. For example you can do engineering in Life Sciences. What do you mean by engineering in the option 4?

[@yisehakg5039]

I have been enjoying your channel for long and it was quite a blessing to have you ….. Um sorry this is too shallow to present it as academia KZbin channel …..,

[@alekhyaganti7940]

Yes, you are very right about Brazil, especially in Bioconversion they are top notch and in fact they developed this idea in 1991 and it is way ahead than UK

[@earlworth]

Andy, so interested to hear your opinion on this. I’m considering an ML PhD and have heard many opinions on both sides of whether to or not, it’s quite disorienting 😅

[@Teilnehmer]

Don't. I am not sure Andy is the best person to talk to regarding ML PhDs. His advice is very general, and in reality the opposite of what he saying is true. What is true is that you don't neeed a ML degree to get into ML. I have seen job openings for bachelors at top tier companies - that were also open for PhDs. This means you will likely not even get a huge financial bonus out of the PhD. ML also has been huge for at least a decade. It has basically been the most mainstream field of entry for a lot of math, physics and other computer science graduates. So in some sense the "good days" are already over. I am working on a PhD in a physical science trying to apply ML (deep learning to be precise) for a use case in this field. My background has been mostly numerical research in graduate and undergraduate work. Real ML research is mostly very abstract, trying to optimize obscure metrics that no one actually cares about. So in some sense I am lucky to work on something where the main body of the work is the actual application. That can transfer to building a real life business sort of sense of what is important when trying to build realistic models. But it also shows me the huge drawbacks of research. Drawbacks of research: You will be very alone. In the real world modern technologies are always implemented in team efforts. The tech world has mostly left academia in the dust. I recently heard a podcast interview with Red Hat recruiters and they basically said that for the first 6 months of an internship or a junior position, they have to "break down" and help unlearn what the former students learned at university. This is of course much more true of a PhD candidate. So if you care about a job where you work on the nitty-gritty details further down the carreer line potential employers can actually quite easily twist your PhD experience against you. In most businesses you will have specialist for each step in the pipeline of a ML application. In a PhD you will have to do everything yourself (most likely). Unlike what Andy says, this does not teach you management. It teaches you self-management. The goals of research are also very different. In research you only care about getting published. It doesn't matter if your result is basically useless; you only need some small novel thing, maybe an irrelevant improvement. So you will not learn how to build production ready models for customers, instead your aim will be getting published. A big part of managing tech work is knowing where to cut corners. In research you will learn how to cut corners for research concerns which are different than real life business concerns. ML work is neither particularly fulfilling or challenging. ML is a very "empirical" science. This means you are basically throwing a lot of mathematical, statistical or preprocessing tools at the problem without much understanding of these methods just to see what sticks. This is very chaotic and unfulfilling, especially when you are coming from a hard science background. As with most fields in science nowadays, research is mostly a huge scam. Fields that get a lot of attention are actually getting worse because there is so much money being thrown at them that nobody even cares if the research proposal is actually worthwhile. They just want to get in on the "sexy research stuff". So you are very likely to end up with a supervisor who will be of no help to you because the money was not granted because of the good idea behind the proposal but simply because of current trends there was a lot of money going around. The supervisor very likely has no genuine expertise (or their expertise is hopelessly outdated). ML and deep learning is also pretty broad already and expertise doesn't really translate from one domain to another. Natural language processing is quite a bit different than computer vision or audio analysis or generation model - at least on the cutting edge level where a PhD will be concentrated.

[@earlworth]

@@Teilnehmer I appreciate you taking the time to write out such a long response. It seems like you have thought a lot about this issue. Certainly there is a divide between producing papers and building and maintaining systems, as a swe myself I know this. However, I had imagined that a PhD in the field would allow someone to stand out from the competition. Nevertheless I have indeed heard about what you mention, how production ml is all about quality data and not coming up with new fangled toys that may or may not be stable once they scale. Are you suggesting 4 years is better spent working in the real world and building practical skills rather than on an ml PhD (4 years in Europe)?

[@Teilnehmer]

​@@earlworth If you are a software engineer and want to work on cutting edge stuff in ML I would advice looking into optimization code for processing and training in deep learning. I recently saw a job opening at OpenAI that was specifically looking for a position like this (they were not even looking for someone with a deep learning background) and in my opinion it's also the most interesting and useful area for this high-level cutting-edge level. At the scale of real impressive AI like GPT models and similar things the processing and computational efficiency of training becomes an issue again. But then it's really all back to classical software engineering for optimization. So deep learning and machine learning isn't even very relevant at this level. The problem with papers right now in the field (and this is especially true if you are using AI for application) is that you can basically just slightly vary a few methods along the very long pipeline of data processing to create "something new". It's basically an open secret that most papers are practically useless anyway (as in a lot of other areas as well). This is really, really sad and also quite disheartening because you must still pour a lot of effort into this work. Very likely though, this is what you will be doing in a PhD in the field. It will give you expertise in a very small niche within the general field. Most likely the actual expertise will be useless, as with most PhDs. But you will learn some useful skills like better self-managment, organizing your own projects etc. But unless your niche is exactly what a company needs by the time you finish (very, very unlikely) I don't think you will have an edge in a lot of areas. On the other hand however, deep learning is one of the very few research areas where companies actually have their own research departments. This is a huge plus over most other fields today. However, research and development is so volatile that you can't really predict 4 years down the line if there will still be companies doing deep learning research level stuff (and it's not like there are a lot of these companies around anyway...). So if you want a research-type of job a PhD can be a good idea but it's also not mandatory in the same way it might have been 10 years ago. There are also certain theoretical problems with deep learning that are quite atypical for fields with such a high reliance on mathematics: basically no one really knows why these deep learning network converge so well in optimization (or training) to these incredibly high-dimensional manifolds. At least that's what I understand from the Goodfellow, Bengio et al. textbook, might be case that there is a more recent answer to this. But even if there is an answer now: the problem is that basically nobody understood a fundamental mathematical issue of the whole field for years and it still produced very good results. So I feel like this has accelerated the trend of prioritizing results over understanding. But ultimately, if your goal isn't academia, and a PhD in this field might not give you a lot of understanding, because this trend has been accelerated in the deep learning community, then it really begs the question: why do the PhD at all? I was very idealistic about research when I signed up for the PhD and in hindsight I have to say I was incredibly naive. I am from a working class, non-academic background and my PhD journey so far was a very eye-opening experience in a very frustrating way. To be honest, I just took the PhD position because it helped me get out of a really bad personal situation. Technically you can start a PhD for a few months and then see if you like it. If not you can still quit. Companies are looking for people who are doing PhDs to give them somewhat research relevant part time jobs (at least in Germany). Research and the freedom it comes with can be fun and intoxicating, but standing at the precipice of human knowledge can also be deeply harrowing. From a financial perspective it's likely not going to be worth it. There is a good chance a lot of work, even in coding and data science (maybe especially ML and data science) will be automated in 4-5 years. So it's really hard to predict anything at these time scales right now. AI could be so disruptive that you might have to consider changing careers completely within a few years. "Nevertheless I have indeed heard about what you mention, how production ml is all about quality data and not coming up with new fangled toys that may or may not be stable once they scale." Regarding this: the new fangled toys are indeed not very useful at most times, but that's also because most areas of deep learning applications in industry are simply not sophisticated enough to be interesting from a research perspective (research will also spoil you in this way). It is true that the quality of the data is what is most important, especially for most industry applications and ensuring high quality of the data or organizing it is also not that interesting of a job. So ultimately it comes down to what you want to do in your life in the next few years. PhDs an give you some interesting experiences but financially and career wise it might not be worth it.

[@whitemakesright2177]

​@@Teilnehmer Great point about "the good days" of AI being past. Coming from a finance background, there is a principle that when you hear normal people talking about the stock market (for example), it usually means the bubble is about to burst. AI has become a meme at this point. Most people have no idea what it actually is, yet they all seem to be convinced that it's the "next big thing." Usually that means that the time to get into it was 5-10 years ago. The problem with a PhD is it usually takes 4+ years. So if you do your PhD in something that is currently trendy, by the time you graduate, the trend will likely be over.

[@M.....................]

What about a Doctorate in Strategic Leadership? Worth it in the academic world?

[@madinabonuazimboeva9992]

What is about Computational Neuroscience?

[@augustodutra3839]

I'm from Brazil and I'm going to start a PhD in Electrical Engineering in Canada in September of this year. My research will be on 6G technology. I hope to get hired at a big tech company. However, as you mentioned, I can return to Brazil at any time to have a "guaranteed" position at the academy. Actually, there is a selection process. However, it is much more relaxed than in the rest of the world, since the competition is small. Wages are very good compared to the average Brazilian salary and there is no postdoc requirement to be hired as a professor at public universities and vacations are paid for 60 days a year. I shouldn't be saying this but it's not necessary to be a Brazilian citizen to get a position in Academia here.

[@shezgill]

Good luck in your studies!

[@kaitnip]

First of all, best of luck to you. Second, I believe it's smart that they don't ask for citizenship. You want as diverse a crowd as possible in your universities.

[@augustodutra3839]

@@kaitnip Actually, there are already a lot of foreign professors here.

[@damerihaanas4513]

Do not do Ph.d

[@augustodutra3839]

@@damerihaanas4513 Which are the other options?

[@anny8442]

How do you think one can enter the AI field from the social sciences perspective? I am incredibly interested in the field but more from the ethical/educational perspective.

[@llbodlearning8591]

My PhD is application of AI in Chemistry. And I am almost jobless. I have no permission for project or research grant.

[@Teilnehmer]

I am in a similar position. Application of AI in physical sciences. Thankfully my project got extended. But it's just very bad all-around. Supervisor has no clue what I am doing. I needed to learn AI and deep learning completely on my own and even if I finish it, the PhD is not that huge of an advantage (if at all) as this video makes it out.

[@swish6143]

How on earth is that possible?

[@llbodlearning8591]

@@Teilnehmer Talent will find its way. God is great.

[@flowerswerewarpaint646]

If your doing AI totally on your own, that's not really an expertise in AI, that going through a math/stats program will give you Yall have an obtuse interpretation of this man. It doesn't sound like either of you are researching ML, but researching another field using ML

[@llbodlearning8591]

@@flowerswerewarpaint646 May be. However research in "AI" and "Applications of AI" have different importance.

[@silverchairsg]

Since a phD takes at least 3 years (if you're extremely, extremely talented and lucky) and more likely 4-6, won't industry demand have changed in 3-6 years time?

[@cedriclothritz7281]

Oh good, I'm defending my PhD in NLP next Wednesday. Glad to hear I didn't waste the past 4 years of my life;)

[@hitriy_evrey]

what is NLP?

[@cedriclothritz7281]

@@hitriy_evrey Natural Language Processing, a field of AI and machine learning that involves everything to do with text, speech, and narural languages. You probably heard of ChatGPT and the recently released GPT-4; those are products coming from the NLP field.

[@Jay-bq6pz]

PhD in statistics??

[@desertezz]

Many of the social sciences get forgotten about in these types of conversations but everything from sociology to political science is akin to getting a Phd in statistics (if you're a quantitative scholar) as you'll likely take mostly stats courses and will develop a deep understanding of stats and data science while you rigorously apply these skills to real world problems.

[@supahottfire]

You forgot Business! its an extremely valuable PHD to have. There's a shortage there and its very interesting work.

[@Gracejohnys]

Question to the commentators: I’m finishing my Msc Nursing this year. What is the best STEM Phd that I can get into ?

[@oleopathic]

Please advice which masters program to chase for a civil engineer with a Bachelors in engineering + license in Professional Engineering in the US.

[@JupiterThunder]

30 years after I got it, my PhD has earned me £0 in additional income. I am now within 7 years of retiring, and I don't expect this to change.

[@marcolee1632]

Hi there. What's your phd on?

[@JupiterThunder]

@@marcolee1632 Laser optics

[@JupiterThunder]

@@marcolee1632Laser physics. I replied earlier but my comment was deleted for some reason!

[@TiernanFitzLarkin]

What about a PhD in AI within the Urban Planning discipline?

[@Mica_No]

Nice beard bro

[@user-it5gu9jx8k]

I’m trying to find universities that have PHD in AI but I couldn’t find one. Could you please tell me where ?

[@michaelvonreich74]

AI/ML PhD is already the most difficult category to get into, in the top universities.

[@whitemakesright2177]

Which probably means that the trend is already reaching its top. In 5 years there will be a glut of AI/Ml PhDs and something new will be the "hot" trend.

[@PaladinLeeroy42069]

I've been completely immersing myself into AI and doing all the research and relevant schoolwork I possibly can, so I really appreciate the validation here

[@erockromulan9329]

One of my favorite books that I'm currently reading is "Data Driven Science and Engineering" by Steve Brunton and Nathan Kutz. It's amazing.

[@temiymahs_World]

Can you get a PhD in cybersecurity without a background in cybersecurity?

[@suhaibalazzeh3255]

lol , i am from Jordan and sadly there are no intuitions that can grant masters degree in Computer science or Cybersecurity .Therefore i went with the option of finishing English Literature but i now I've realized this is like one of the worst things I ever did .

[@sujithcooray3162]

How about physics !!. What kind of fields in physics has more opportunity ??

[@mihuq747]

Research, many countries and more so of the big ones such as USA, China, Germany focuses a lot on new advancements. Through warfare and even new forms of energy

[@jacquesiv5054]

Hi Dr. Stapleton, I'm a senior doing a chemistry BS in the US and I have a lot of questions. Should I apply for PhD program in Chemistry (physical chemistry/computational) or go to R&D industrial jobs. My advisor is from New Zealand and he introduced me a few school in Australia. I really want to talk more with you. Can you share your email? Thank you.

[@Balbs77]

I did my BS in chemistry and have worked in pharmaceutical R&D for the past 5 years and am planning on going back for a PhD. When talking with my coworkers who have PhDs, they told me that those in their cohort who were in the industry first had a higher level of focus and wisdom about them that enabled them, on average, finish their PhDs faster and have the greatest number of job offers.

[@jacquesiv5054]

@@Balbs77 Thank you so much for sharing. I have very little research experience right now :( and I'm already a senior. Do you have any tips to apply for a R&D job? I really love research.

[@Balbs77]

@@jacquesiv5054 I don't think I can come up with an adequate answer for you but I can tell you how I did it. I did not have research experience myself upon graduation and didn't know what I wanted to do. I applied for a QC chemist role (a polar opposite of r&d) for a small pharmaceutical company. That role was very rigid and the SOPs were well defined, so there was no room for any research creativity. Fortunately, working at a small company enabled me to get real good at troubleshooting instruments (small companies don't have the budget for internal instrument shops, and vendors don't prioritize smaller service contracts). After some time, I leveraged that knowledge along with the knowledge of Good X Practices (look up GxP if you're interested) to get a position in a small molecule CMC R&D department at a much larger company. I've been there every since

[@Balbs77]

@@jacquesiv5054 I will also be very honest with you, you're going to have a difficult time getting a physical chemistry job in industry period, even with a PhD. Computational stuff is valuable. With a BS, you are more than likely going to find yourself in an analytical role. We have solid state and process chemists who have backgrounds in pchem, organic, and chemE at my work, but their functions do not hire anyone without at least an MS

[@Balbs77]

@@jacquesiv5054 last piece of advice. It pays to be good at mass spectrometry

[@drihayere]

PhD Economics is TOP

[@benjaminmathis8839]

What about PHD in Clinical Psychology

[@Karmawillgetyou]

What’s your opinion on PhD in Epidemiology ?

[@aniksamiurrahman6365]

Wow! Very good video idea.

[@haunting33]

Phd in marketing ...ur opinion ?

[@joaovitorbueno241]

Hi Andy, what do you think about climate change-focused PhDs (courses like oceanography, meteorology and marine biology)? Are they good options nowadays?

[@aniksamiurrahman6365]

Very good video idea.

[@thefaramith8876]

Ah yes, humanities and social sciences are in the dustbin again.

[@mahanvazsilva112]

Yeah... 😢

[@uwamahoroemile694]

Not really , You can orient your research to these field of better PhD and work along with them

[@sakjdh]

I think PhD in AI with focus on financial market is a really good one.

[@crypticnomad]

I am starting to think that a PhD in underwater basket weaving was a poor choice

[@oluwajuwonloowojori8049]

What of Demography

[@jimstiles26287]

I got a PhD in Civil Engineering in 2000. I have not used it since.

[@jimstiles26287]

My specialization was in fluid mechanics and rheology.

[@eduardomartinezcrucess8189]

They wont allow me to register on a Dataciencie Phd if not into Data science major nor college degree, not new job without experience i´am 35 years old and forgetting about all my life and social science education expertise is a bit depressing honestly. I still cannot find niche where I could fix my career into a new data science landscape with my current job experience. Sometimes carreer advice forgets about us, people from life sciences and social sciences.

[@aperkins07]

Math education seems too niche no? Think it makes more sense to do a math PhD as a math PhD can always teach math subjects. Other than that, interesting as it seems to reinforce what my cousin is going through with not enough academic positions so competition is extremely high

[@jakkritphanomchit]

A PhD is niche by definition

[@livinghomunculus657]

2:30 industry doesnt hire data science phds

[@eduardomartinezcrucess8189]

Everything is data science, how about people with life sciences education? Are we doomed to unemployment? What we could to achieve satisfaction on a valuable PhD?

[@Drganguli]

Engineering PhD’s are the best but they are hard to complete with most advisors being highly draconian

[@247AI-sp5zz]

I think a PhD will become a Bachelor's Degree in the coming 10-20 years, it won't be worth like today but still worth it for a Career 😂

[@uaiteprimeiro223]

If doors mean money, we should take these 3 or 4 years learning how to get and manage money

[@HeroinesHeroH]

I'm 30yo and going towards a ms in social sciences. While I enjoy the field (media) I cannot stop the thoughts of being a 30yo with one really really expensive hobby. I really wish I was more orientated in tech and hard sciences but oh well life is a lottery.

[@Militaizi]

Andy you're not taking into consideration one thing; PhD in these fields, as they're in demand is not necessary. I got a position from AI which is traditionally a PhD position, because there are not enough canfidates to fill the positions. So instead I would say these fields are good for any education.

[@yakaridubois3378]

The fact that you oppose science and humanities disappoints me. Humanities is science as well. Anyway most of Andy's advice are oriented toward shifting from academia from industry, not surprising for a chemist.

[@medearina]

as a fresh masters' student in economics who's slowly transitioning socially as a trans woman (i am one) your videos are incredibly informative to me, Dr. Stapleton. i'm glad i discovered your channel.

[@ExpatTraderFX]

Nobody cares why do you people find the need to tell everyone your personal business...

[@user-ii7um5zl8e]

>last How naive...

[@lucabonaccio]

Rip for biology PhDs