The /sci/ has often discussed studying for a PhD and the career choices as well as what to keep in mind. The idea of the general was to have a common place for the discussion and also build this document with hints, recommendations and suggestions. After one discussion on PhD in Physics as a meme, your editor opened the scg general October 2020. For reasons unknown, the mods took a dislike to this, so all such discussions were moved to the "stupid questions thread", >>>/sci/sqt. Lately the career general threads is permitted again, under the name /scsg/ – STEM Career Support General, or the name STEM Career General – /scg/. Hopefully it will remain. Lately it has been commented that there is a bit much doomer posting. For all the problems you will encounter, remember most people find doing a PhD was worth it. Just don't expect an immediate pay-off.
This general has now a lot of regulars and quite a few with a PhD. Thankfully most by far are happy with their choices and journey through academia. This comfy general is archived on Fireden.
The discussions are about science careers including PhD, postdoc and the escape from academia to industry. I, your editor, was insanely naive when I did my PhD in Physics and with all the glossy info it can still be hard to find the brutal truth. A lot of the text below is cut and paste from various contributors with light editing. Many headings below need substantial fleshing out. Currently it is a bit Physics heavy but all research fields are meant to be covered.
First of all, know what you are getting into. Doing a PhD is a long, hard slog and requires a lot of perseverance. Make sure you get a stipend. Get good grades so people will actually want you. The more you are wanted, the more leverage you'll have when it comes to stipend. Don't haggle, justify why you need that extra cash. There are three main ways to do research (based on Physics and also ChemE):
This is the classic image of a guy with dishevelled hair holding a piece of chalk in front of a blackboard.
Advantage: if your chalk breaks it costs next to nothing to get a new one.
Disadvantage: it is harder to get a job in industry with a purely theoretical background (and you will need a haircut).
This is mostly simulating how things should have been according to the (incomplete) theories.
Advantage: if your computer breaks you log into another one. You should be quite certain to complete the PhD on time.
Disadvantage: few, mainly that you miss some experimental aspects
This is the classic image of a guy with dishevelled hair holding a piece of recently exploded equipment.
Advantage: this probably gives you the best escape route to industry. Some consider explosions a plus.
Disadvantage: higher risk of failure due to equipment failure or accident. Some consider explosions a minus.
Do a background search on professors, citations, h index, relevancy in the field, impact factors of the journals they publish in. If a guy publishes often in Nature, you might have a chance to publish in Nature too. If the guy is good, he probably has money, which means more conferences. Conferences are great for networking (and a perfect place and pretext to hook up with some cute Chinese PhD student). Also make sure your professor is not featured on Retraction Watch. Fraud is rampant and a database was needed to keep track of the sheer volume. Also check Science Integrity Digest and the PubPeer database.
Some important and counter-intuitive advice based on the experience of a fellow anon (alias "ChemE-anon"): DO NOT aim to get a high h-index professor. I made this mistake. My professor is a top 100 h-index Leibniz prize winner. My Prof. is brilliant, the cons heavily outweigh the pros in my opinion as I outline below:
When I started I was told that the he will not make time for me until my manuscript is ready (for those of you who don't know this mean that your first research project is already ready to be published). I was fine with this, it suited me even, but what I didn't realize at the time is that my first manuscript had to be Nature potential or equivalent. Publishing anything less is not worth it to your Prof. because it will just lower his IF. So every paper he puts his name on will have to at least stand a chance of beating his lowest top 20 paper for citations. This is not good for young PhDs who need to get as many papers out as possible (you should aim for at least 5, but realistically you need 10 to be competitive, aim for Nature with 1 – 2 of those).
It is better to apply to an associate professor who is still just starting his career. You will be allowed to publish faster (and garner citations/attention while you work towards your Nature-tier cap). Many of my US collaborators are like this and they all have jobs at IBM and Google lined in their second year already.
It is important that the professor is experienced. One anon noted that:
>Go for experience profs who've had plenty of PhD students in the past. The single most important thing that determines your PhD experience is how good your supervisor is.
>My supervisor has been at his university for 30+ years, which means regular meetings, lab reports, and a structured plan for my PhD. Takes away so much anxiety to have someone know what they're doing. You don't want to flounder around for years with an incompetent supervisor not knowing wtf you're doing.
Getting statistics on this depends on the country. There are central repositories for national theses in Australia (including contents from New Zealand), Germany, Sweden, UK, USA (including contents from Canada), and some universities such as LMU München have their own databases.
Also make sure the professor has a good track record of having students graduating on time. Some professors, especially on the Continent, see students as cheap labour and intentionally delay their graduation. Avoid these at all cost as this could cost you time and money, and you have little of either at this stage in life.
Research covers many fields, from biology and chemistry to physics and mathematics.
This field pays well. One anon notes it is "Because there's not that many people doing it and biotech and data tech are booming. You need a postgrad in bioinformatics or something closely related. That's the other reason it pays well, data science pays well but has an influx of "data scientists" who just went through a coding and data bootcamp, bioinformatician roles are pretty much solely for PhDs or at least masters grads."
Another noted that
Advice: As a math major, take biochem seriously, try to audit a lecture in it or something like that. Knowing even a few basics pays off immensely. Stryer is the classic textbook.
Also, try to get to know the biologists and their way of thinking. Its quite different from the way mathematicians or even statisticians normally approach problems.
One anon reported in:
>What did you do it in?
>Why did you do it? (career paths specifically)
Personal drive mostly, but also wanted to get into R and D and the applications are truly rewarding. It felt good to contribute in a meaningful way in an applied field.
>How was / experience it?
Good, hard work. Rewarding. Opened opportunities. Pretty stressful too.
>Would you recommend it to someone that purely wants better income opportunities?
Depends on the person. Opportunities in a particular field may open when you get an advanced degree, but so can experience. Ultimately, you really need to want to do it (a drive for increased income is a perfectly fine reason) when things get tough. Also, career focus is less concerned about prestige but also means you will have some settling to do between what you want to work on and what you get to work on.
Responding to the same question as above, another anon reported that:
Cancer is interesting and there is a lot of funding and projects in cancer research
Still doing it, it's decent, nothing to complain about
If you're doing it to get into pharmaceuticals, just pick any project in which you work on human diseases in human cell lines and human tissues. And pick something that interests you so you won't be bored out of your mind for years.
Douglas Comer has advice on a career in CS.
The job market for ecologists is highly competitive right now. This is due, in large part, to saturation by new graduates and later-career researchers waiting longer to retire from their positions. That's not to say it's impossible to get a job, but you need to make yourself stand out to be remotely competitive.
In my experience, I've noticed three key points that increase your ability to compete for those precious few opportunities. First, a postdoc is pretty much universally required. This is especially the case for academic jobs - you need to have demonstrable proof that you can complete projects and publish on them. Second, developing strong quantitative skills means you can work on any project, in any system, and with any data. This is huge in increasing your potential to work outside of ecology and pairs closely with the third point. This third point is to become proficient in statistical programming, most likely with R software. Being able to code also increases the width of your marketability.
To illustrate these three points, consider that a very capable researcher (with 2 postdoc experiences) I collaborated with when I was a postdoc ended up taking a position with Wells Fargo where he conducted financial risk assessment analyses and modeling to inform lending decisions. He was working completely outside his ecology background, but was leveraging his experience and skillset to make over 6 figures in that Wells Fargo job.
With a PhD in mathematics, the cliche question is of course, what am I in for? Will I get a $300K salary afterwards? And the answers are not too shabby:
Unironically yes, but only if your are studying something that could be considered some form of data science or financial mathematics, and you have a lot of coding experience.
My department is heavily focused on applied math, and a lot of the dissertations in recent years have specifically been on the statistical analysis of natural language and on using graph theory to analyze data from social networks. I don't know if they're making 300k a year, but I'm sure some of them are easily making 6 figures out of grad school.
Of course the 300k starting salary is just a meme, and it's extremely unrealistic for most math PhDs, but there are some subfields of math that could conceivably land you a very comfortable position in industry right out of grad school. If that's the route you're interested in, then you should probably focus on stuff like probability and combinatorics and differential equations, rather than topology or number theory or algebra.
Friend of mine, has a PhD in Math, works for a Wall Street FinTech company, has a base salary of $200k/year, and makes an extra $50 - 300k/year in performance bonuses.
The tech and data revolution is making this a reality for Math PhDs. General wisdom dictates that getting a PhD makes you overqualified for industry positions and that may still be true for the most part. However the last decade saw the rise of the 'scientist' position. Research scientist, data scientist, etc.
Let's just call it a corporate scientist. Corporate scientists change the game because traditionally a 'scientist' is a Ph.D. so companies realized that they might as well hire real scientists for these positions.
This new economic paradigm is quite interesting. Let's be real here. You, as a Ph.D., know fuck all about the real world. But your Ph.D. certifies that you are smart and driven. If you get hired for a corporate scientist position you will be put under a high-ranking VP. This VP will likely have a STEM background + an MBA (very common for VPs nowadays). That allows him to speak with you, but also speak with C-suite and investors. He will usually guide your work giving you very hard problems to work on and, if you are smart, you will solve them.
My current assessment of these corporate scientist roles is that they are very stressful. They will pay a lot to hire you, but they don't hire many of you. In a division you could have as little as 2 scientists working under a VP. As such you will be overworked but hey, now you are in the top 0.1% of earners. Congrats.
These in particularly is oversaturated and competitive. Usually graduates who enter our programme will already have 1 – 2 RAs and produced good research in their final year, usually by building on confidence from having proposed and implemented their own ideas in some.
>I was lead to believe that there was virtually zero potential growth in Pharma/biotech industry for somebody with a BSc
They are right, but the best route is to do your MSc/PhD through their company that is the only way you will actually find employment (to get that opportunity you have to really excel at your entry level role too).
The other alternative is if you do an amazing PhD on the tier that it actually brings you fame in the industry (yes, this is possible). But that is far, far less likely than the first option and in particular if you don't have a solid plan/motivation/topic then the probability of doing a good PhD is almost zero. Like the other Anon said PhD grads are in oversupply and your CV is far more likely to get tossed than someone with professional experience at a company. Never underestimate the value of experience. It is worth far more than degrees in general.
If this is all difficult for you to reconcile it is because there simply aren't many positions in the world that actually need a PhD (or a scientist in general). You should really consider your degree an entry point to a company where you can gain experience in a particular industry rather than proof of a valued skillset (it is not valued).
Another anon followed up with
From my experience in medical devices yeah. That said, once you get to a certain level you either need to go into management or have a postgrad for the higher roles.
Derek Lowe reports that in the field of biopharma, The Money Keeps On Flowing In. The financial situation with continuing low interest rates means big money is looking for places to invest, and with COVID-19 biopharma seems hot. This might not last.
Physics comprises many fields, from astrophysics to solid state. At first glance this could look more limiting than studying engineering but several anons report of pivoting with ease into other fields. One anon declared boldly that
> Physics provides the ultimate base to pivot to any of the engineering disciplines.
Another stated that
> I am a physicist that had to pivot into electronics, into software, into quality assurance and more. So yes, a background in Physics is a proven excellent basis for pivoting, multiple times too.
Job market after completing a PhD is tough.
Job market in industry and academia is good, as the semiconductor and sensor industry will continue for decades.
One anon reported that domestic students are government funded and can usually get a stipend of $28,597+ as a full-time student. Most research groups with supervisors who also teach will give their students part-time jobs as demonstrators/tutors as well (~$48/hr last time I checked but you only work during the 2-3 hour classes). There is also a Vlog by a PhD student in Australia commenting on life as a PhD student and what is to follow.
One anon reports that the French is obsessed with the age of students, so starting a PhD late is a no go.
Germany, like Switzerland has 70k (USD) salaries if you get a 100% employment contract (usually meaning you are employed by the state as a scientific researcher, but it's a myth that the state ever asks you to do any work, you get to work on your PhD full time, unless you are 50% paid WIMI by Prof. and 50% paid to TA etc). Usually engineering PhD positions especially at Fraunhofer labs pay 100%. Physics and other sciences is usually paid at 60%. More prestigious universities and national labs either pay 0% (you pay out of pocket) or a maximum of 60% at Max Planck Institute labs. A special case is TUM which has a 2000 Euro (tax free) scholarship for all PhDs.
One anon notes that not all German 'Hochshule' award master's degrees. Some 'Hochschulen' have university accredited programs. The degrees such programs bestow equivalent to a university or technical university degree, at least on paper. It is unclear how a 'Hochschule' will impact your later opportunities in pursuing a PhD study. The following comments were made:
You'll have a MUCH harder time being accepted into a German universities' master or PHD program. As for the job market, employers usually subtract 0.5 grades from a Hochschul-degree to get the equivalent of an university degree.
Another disagreed andwrote
It used to be much harder but nowadays it has become much more common. Some universities will be tougher than others. Usually you have to take some extra courses along your masters degree "Auflagen" That can range from a few courses to a fuckton depending on the university and field. And some universities directly admit you with an FH degree
A third stated that (edited)
Hochschule is the word for general higher education institutes in Germany. You have Fachhochulen and Universitäten which are both "Hochschulen" Due to the bologna process Fachhochschulen were legally set to the same level as universitäten for the most part. So most renamed themselves. A few "universitäten" still kept the name Hochschule like the RWTH Aachen or ETH
They are usually regarded fine and acceptance increased more over the past years. When it comes to masters programs it hugely depends on the amount of credits you have in particular areas and the field you are studying. Some universities will directly admit you to the masters and others want you to take some courses to fill the gaps
You can find jobs just fine with a Hochschul / FH degree. However kt's much better if you do a "duales studium" in conjunction with the hochshul degree. If you do that at a notable company you probably beat graduates coming from traditional universities easily
In summary, this is complex.
In Norway it is possible to get funding for doing a PhD while being employed in industry, called Nærings-PhD. There have been several ugly stories in academia, such as a professor locked out from his work and a postdoc having her work taken by a professor. For a small country, the conflict level is high.
Some anons report life is good, but pay is surprisingly low compared to the US and even places like Germany and Switzerland, especially considering the cost of living. Unfortunately there is a ceiling for highly-skilled individuals. Also there is no real innovation in Norway either. There are a few spinoff startups from NTNU or UiO but their business rapidly goes to China anyway. Industry jobs are not stressful though.
Starting PhD salary in the UK is 12k; GBP 15.2k and it increases with RPI annually. Some programmes increase it to GBP 18k if they're well funded. Also industrial PhD pays more. Not sure of any PhD making more than 18.000. One anon mentioned 15k. You can get more as a TA but might have to compensate the PI for the lost research time with more work during weekends. PhD students in the UK are usually funded through scholarships and not teaching assistantships like in the US, so funding isn't assured to everyone who is admitted. Statistics for Cambridge is available. Academic pay is regulated by the HE Single Pay Spine.
It appears that from summer 2021, students who graduate from undergraduate or master's programs will be able to stay and work for up to two years and PhD graduates will be able to say for up to three years. After that you need to switch to a work visa in that time period aka you must get a job and your employer must offer to sponsor your visa. Otherwise, you're kicked out after the time limit. Before considering staying, you should review the salary levels in view of your field and also institution. Salaries are good to adequate provided you graduated from Oxford, Cambridge, Imperial College or similar level institutions. After the top 3 or 4 institutions the salary levels plummet. Computer Science and Economics pay fairly well, but EEE and Physics salaries are plain bad and you should just go to another country.
Research Experiences for Undergraduates (REU) is available at several sites. It was described by one anon as "REUs are real and legit. Some people may argue how useful the research that comes out of it, but I would say that it gives you a taste of what research is like." Another noted that in general, REUs are not better than local research, but that "the benefit of research at your school is that you can get deeper into the work until you're actually somehow connected to relevant things. however, REUs are still good. if you have no other option (due to availability at your school) then REUs are amazing. if you get one with a good group in your field, it can even be better than spending a summer at your home school."
Many work as a TA as a PhD student. This can be useful experience and also a source of income. In today's problematising climate it can also be a source of accusations of impropriety, even decades later. During a discussion in this general the following steps were recommended to protect yourself:
We try to avoid doomer postings here, but one anon reported he had been fired from an internship due to accusations. Do not take this lightly. An accusation 20 years later is one you cannot defend yourself against, it will be her words against yours, unless you follow the advice here.
There are a few web sites with general advice such as the /Sci/ wiki and the /Sci/ Guide, though the latter suffers from bit rot. The PhD Grind is worth a read. There is also The illustrated guide to a Ph.D. Recently a link to a repository of links with advice was posted.
There can be many reasons. First of all you are still young, most likely have no attachments and should be free to travel wherever. Postdoc pay is bad so you have little to lose in going elsewhere. It is also a good time to go abroad to widen your horizons beyond technology alone and your brain is still young enough to pick up a new language or two. Knowing foreign languages is a major plus if you go to industry. In any case, life is also about new experiences, and a postdoc abroad ticks all the boxes.
This is also about networking, and going from a university to a different place develops your network, perhaps in a place that is more international. This was the case for your editor, going from red brick to a large national research lab in Tsukuba, Japan. This was a fantastic experience, can recommend.
It is also important that you leave your professor. If you stay you will be treated as his "student" forever. You will get some early promotions, sure, but you will also stagnate. There is also the risk of increasing academic inbreeding, and I have seen that myself. They had to interview me but knew they would reject me, at the time I was too naive to understand this so I was annoyed they hired a guy who was not even finished with his PhD over me who already had a PhD. In hindsight I think it was a good thing I didn't get that job.
Do at least one postdoc, preferably in different countries. Make sure you try to learn the language. The purpose of doing postdoc around the world is not just to stay in the lab and make results, it is also about building a network. Language skills can also be useful if you go to industry.
For an academic career, the purpose of a postdoc contract is to get as many good publications as possible. For this reason it is important also to consider the publication potentials. A comment:
for a postdoc you want a position that will help you get papers. in my experience, it's not great to postdoc in a brand new experimental lab unless it's one that can get set up in less than a year and start taking data.
So it is not enough to check the publication record of the PI, you also have to see where those publications were made.
In Japan you have several postdoc fellowships available. And you can chose between academia or national laboratories. Academia can be a bit feudal where the professor is your local warlord and you need to learn some Keigo. National laboratories are more relaxed. Many are located in Tsukuba, a relatively new science city. There are two main groups of foreigners in Japan: scientists and English language teachers. Some have been known to go back and forth between research and teaching. There is a Wiki dedicated to Tsukuba.
Also: Let's Speak English is an autobiographical comic about an English Teacher in Japan. If you learn Japanese you should consider taking the official Japanese proficiency exam, Nihongonouryokushiken. It is quite realistic to pass the lowest grade after one year of studies, and the second lowest grade after another year of studies. These are part time studies that come in addition to work as a postdoc.
You can do your postdoc in academia or a national lab. A few comments:
National labs are great if you like the field of research. More reliable funding than academia, comfy job and benefits, no teaching. They're mostly in nice areas to live too. Only downside is that you don't get to pick what you research and you're not guaranteed career growth, so if you're not careful you'll stagnate
I did a postdoc at a national lab in Japan, can recommend. Universities can be a bit feudal where the professor is the war lord. In national labs, things are more relaxed.
Expect to do 2 – 3 postdocs lasting about 2 years before a realistic chance of tenure. Competition is brutal. Nepotism and academic inbreeding are not uncommon. In some places (such as Taiwan) there are rules in place to avoid academic inbreeding while other places use it openly for empire building. Check out the background of the people working there before applying; it could be a colossal waste of time. Make sure to search for "academic inbreeding" and also conflicts relating to Employee Inventors Act in the respective countries.If you stay in academia, be aware that the pyramid is tall and narrow. Academia is super competitive. "Academic politics are so vicious precisely because the stakes are so small" is a quote with many variation and attributions.
Most people start the postdoc career without a thought about retirement, thinking that will be in the far future. Just keep in mind that in many countries, a short term contract means you are allowed to pay into the pension scheme but crucially you will never get a penny back. When you start pushing 40 you should look into this and consider pulling the trigger for a career outside the postdoc thread mill.
ChemE-anon notes DO NOT do a postdoc, it will definitely harm your career if you fail to get into full time academia after. You should aim to start networking heavily at conferences and through your professor in your final year. Also a PROTIP is that PhDs can still do internships at R&D departments. This is more than worth it if you do well you will get your 6 figure starting salary when you graduate.
As for the job market, the good news is that there are a few industrial positions that only hire PhDs, especially in pharma, aerospace, computational chemistry firms, big data etc. The bad news is that there are far more PhD graduates than open positions. Look for universities that have strong ties to an industry you want to work in and do not just at the most prestigious universities. I've met Stanford and CMU grads that are unemployed. You _need_ to work your network for a position. About 1 in 10 PhD grads end up working for really cool companies in areas like defense, aerospace or pharma. About 5 in 10 get low salaried positions at startups (battery companies, specialist industrial equipment) and the rest do postdocs. This is less gloomy than the undergrad picture (everyone is employed in an actual STEM position).
The sticky mentions patents. Be warned that at most labs patents you develop belongs primarily to the lab. You might get some royalties for it, but you can't usually start your own company with it or sell it to Musk.
In general I would recommend you follow the meme trends. Even big, serious companies jump on the naive hype train and hire you. Ten years ago a lot of firms hired on the "nanotech" buzz word. Today if you get some kind machine learning publication at on of the top 3 conferences you will likely get a good position somewhere. Quantum computing meme is also hiring. One final note of advice: don't waste your time posting about major politics on /sci/. Where you publish matters far more than the discipline on your degree.
One anon asked this question, and the advice can be summarised as follows:
A frequent escape route for scientists is intellectual property (IP), either as a patent Examiner or a patent attorney. In this profession a PhD is normal and also appreciated. Information on life as an Examiner at the European Patent Office (EPO). Unofficial figures are that 30% of examiners at EPO have a PhD. Salary is high and since the EPO is an international organisation, employees do not pay taxes (other than a 2 % contribution to the internal retirement fund). Also United States Patent and Trademark Office (USPTO) is hiring. Both employ several thousand Examiners, and just to keep up with retirements alone will have to hire new people continuously.
Very roughly half new hires into the patent profession are former Examiners, half come from industry. Few are fresh graduates. Also only few patent law firms recruit Examiners from EPO since their salaries are rather high and hard to match.
Management consulting (MC) has many facets which have one thing in common: management. Management consulting subsumes strategy consulting, which is the most prestigious section of MC. There are other sections of MC like technology, risk management, advisory (often financial, sometimes strategy), or IT.
Tier 1 is known as MBB (McKinsey and Company (AKA "The Firm"), Boston Consulting Group, and Bain & Company). Hardly anyone is going to be able to get into a T1 firm, though they recruit a wide range of graduates practically continuously, and word wide. Some, such as McKinsey, recruit fresh graduates including people with research background and PhD. Before joining it is important to read up on how these firms work, especially the "up-or-out" policy. While very competitive these firms often promote intellect rather than years of experience, offering a way into this profession. McKinsey publishes the McKinsey Quarterly which can give you some impressions about the work.
Accenture, AtKearney, OliverWyman, etc. are tier 2, and the MC divisions of the big 4 accounting firms are tier 3.
The important factor about MBB is that they are considered purely strategy. So if you for instance are good at data science, you would be brought into Accenture on their tech side. At McKinsey you would be matriculated into their newest class the same as everyone else but would be staffed on their data science projects since that is in your skillset. Note, however, McKinsey Quantum Black and BCG Gamma for the latest offerings. One anon stated that:
MBB isn't purely strategy, there's plenty of implementation but it's boring. Quantum Black and Gamma are cool if you really just want to do data analysis, but you're a second class citizen in the firm and the job isn't as good as other data jobs.
Besides being considered the most prestigious section of all consulting roles, the benefit of management consulting is the fast track to management and exit strategies. In industry it might take someone 5 to even 10 years to reach senior management. Whereas in any management consulting firm you are pretty much guaranteed senior manager by 5, and the higher the tier the quicker that happens. At McKinsey, for instance it's possible to make senior manager in as little as 2 years. Over the years you will have built connections at various companies, again the higher tiers will have better clients, and you can decide to jump ship into industry at senior manager or just manager if you really hate consulting (many do).
One life sciences anon recently signed offer for MBB consultant as a STEM PhD, and reported the following (lightly edited):
>formal background in maths
Unless you join specialist tracks or QuantumBlack/GAMMA/whatever, the maths is basic arithmetic and and high-level financial models, it's not a quant investment bank
>what the position entails
You are hired as a generalist management/strategy consultant, not in any particular industry. So you are staffed to projects with, say Oil and Gas companies, or Pharma, or Kraft Foods or whatever, where the company has some business strategy question ("How should we expand our cheese business" or "Our profits are declining and we don't know why") and then your team figures out the cause and how to fix it. They are hiring PhDs at the same level as MBAs because they expect you to have learned structured problem solving skills, they don't care about the content of the degree at all.
>Process that led to the position:
This is specific to PhD/MD/JD advanced degree intake, for undergrads I think you either have to currently go to a target school (Harvard, Yale, etc, there's a list somewhere) and apply through on-campus recruiting, or get a referral from a current employee.
For advanced degree, you simply either submit your application to the website or do some LinkedIn cold calls and get a referral from current employees. Full time applications were already due in July or so, and you need to do it while still in school. They also have 1-7 day summer programs trying to recruit advanced degree students called McKinsey Insight/Bridge to BCG/Bain ADvantage with deadlines in April or so to give you a chance to see what consulting is like. You need to generate a 1-page business resume for any of the applications, so really focus on that, most of the work is even getting an interview in the first place.
They do fit questions ("Tell me about a time you resolved a conflict") and "Case interviews" which are essentially actual projects boiled down to a 20 minute problem that you solve in the interview.
There are many resources for learning how to do case interviews, I liked the free 7-day course from Crafting Cases and then there's a book you can find a PDF of a book called Case in Point. A big part of the interviews is making a "framework", essentially a roadmap of how to solve the problem before actually diving in, and many people just memorize stock frameworks from that book but really you need to have more flexible ones you can use in any situation so you don't look like an uncreative robot
After that you really need to start practising so using a site like Case Coach or PrepLounge to find people to trade off being the interviewer and interviewee with (for free, or pay $$$ for coaches if you're rolling in it), some people do like 5 cases with randos and get an offer, some people literally do 100s and fail. I did about 40 because it's a totally different mindset than PhD (have to be comfortable with ambiguity, proposing a strong recommendation based on very little firm data, only running down the most important leads) and felt ready by the end.
This anon also notes that at least US MBB offices have target schools but this is not entirely official. Some statistics is available. There is also the 2021 ADC/APD Summer Programs/Full-Time Applications Thread with a list of companies.
It is important to note that MBB tends to operate on an up or out-policy. One anon noted that:
Every 2 years you will either be promoted or fired. It breaks down about into even thirds between promote, fire, and quit. The promotion timeline is insanely fast. In your third year out of PhD you will be a manager making $300k, 2 years after that you're pushing $500k. It just keeps going up until you bug out.
You will be evaluated every 6 months and promotion/firing will be every 2 years.
One anon mentioned that a PhD is required for research and development activities in this field:
Industry science jobs. Can't go above research drone without the qualifications. Some of it is even built into the requirements for medical research.
Medical devices. I'm not sure which country the requirements come from but we submit to the FDA (US), EMA (EU), TGA (AUS) and Japan/Korea/China but I have no idea what their agencies are called.
QA were telling me there's certain docs you can't sign-off on unless you're a postgrad chad.
I don't see much in the way of career progression available unless I moved into management or into engineering instead of research.
It is perhaps close to a cliche, that science graduates can get into quantitative analysis and earn obscene amounts of money. Two quant-anons commented that:
>specifically quantitative analyst at a hedge fund
I was a quant analyst at a very well known GM fund for a while. Pretty decent and fun work, but you sell it way too hard. Like any job the gains you make your employer pale in comparison to the salary, at least until you become PM and get some risk exposure.
I've realised that the true answer really is taking the startup-pill, unless you are horribly autistic and prefer being told what to do forever.
>only for the top students at top schools
this is generally true, but not always. There are always the odd people that come from tier 3 unis (I know someone at Millennium who did that).
>also what do you have to train yourself in?
AFAIK nearly all big shops (outside of a few like Jane) use Python for the quant infrastructure. So get amazing at Python / Stats first. Learning fullstack also doesn't hurt if you are in more of a generalist role (I was mix of tool dev and systematic strat dev during my time).
Start recruiting. The people who get top jobs out of uni have usually been groomed for that position their entire lives. They started doing internships since their sophomore year and usually have some awards like IMO medals. But if you aren't this then you may have to lower your expectations and recruit for simpler roles.
If you want to explore a bit, JP Morgan always has a huge list of open jobs and their search functionality is top notch so you can easily find everything that is out there in the market and filter specifically for what interests you.
>(only top students from top universities?)
It is and isn't. If you are not the best of the best yet you can build yourself and eventually your experience will beat out any 'natural' talent. And it is true that most places have an attitude that if you are a mathematician they can teach you finance so you should focus on actually being smart first. But if you can apply that on your own to finance and, for example, create a trading system that is an improvement. Specially if you can trade it on your own in a small scale and build a short track-record (3 months to 1 year) of profitability. Then you'll be a top candidate.
>but you sell it way too hard. Like any job the gains you make your employer pale in comparison to the salary
This is true for any job. And if you are getting paid well then why should you care? Eventually you can get a share in the fund and enjoy the true benefits but if you are getting paid 200k+ a year you are already living pretty well.
Generally, this topic is frequently discusses in this general.
With a scientific training you can do great work here. That makes you bearer of bad news, and if you have integrity this will be an interesting but short career. The rest of the story was a doomer post and will not be repeated here.
The military industrial complex likes to surround themselves with an air of sophistication, and add "advanced" to anything. That does not mean reality is close to the image.
Advice is that for RF (radio frequency) work you need a masters degree and DSP (Digital Signal Processing) requires a PhD. Job market was earlier dominated by defence but these days also civilian communications is big, with mobile phone technology companies such as Qualcomm working on DSP chips and algorithms for RF, audio and images. One anon noted that:
DSP combined with embedded/fpga design is a powerful combo, even as an undergrad. Defense companies will be all over you. At smaller companies, this will involve DSP algorithm prototyping as well. I can't speak for RF, but I've heard that since RF is in such demand for engineers at experience in school could help with getting a job. This could be bs though.
This field is red hot, but also a meat grinder with long hours. It is an even more recent field than the software industry, and it shows. Entry and work is simple, because, in the words of one anon:
Probably. The work is very easy, but think about how many people are absolute dogshit at basic statistics.
Even other people in STEM are absolute dogshit at statistics which is why a field that is literally applied statistical modeling is so popular right now. People are just really bad with statistics and data.
Anyway you gotta be quick about it though. I think in a year or two the field will be over saturated. You should be looking at fields that haven't been memed in years to jump into. Personally, I know my niche and I know it's about to become very HOT because all the people in it are 50+ years old. You should be looking at the fields in these sorts of position if you want infinite job security.
Lots of maths graduates go to data science, but you also have to be able to program.
When applying for a job in industry or academia or for a PhD study, you will need a cover letter and a CV/Resume. This is a three stage rocket: the cover letter is to get the receiver to read your CV/Resume, the CV/Resume should get you the interview, and the interview should get you the position. Remember that in industry you will have to get past the HR department, and several anons noted that HR often does not understand the terms, fail to understand synonyms etc, and in extreme cases will believe a PhD is a kind of bachelor's degree. It will therefore help to get past HR if you use terms from the (job) posting rather than synonyms. Remember the world is full of well qualified people, so make sure to add at least something that make you stand out from the crowd. Volunteering and awards are some examples that will help.
Resume is the US term, in much of the rest of the world it is CV (Curriculum Vitae). It is recommended to keep this down to 2 pages. One (US?) anon notes that:
> It's just the standard format, you list your positions and maybe leadership experiences with 1-3 bullets each. I have a 1 page resume and a 5 page academic CV
Confusingly the US also uses the terms 'Academic CV' and one anon described this as
> Lists every single accomplishment (papers, posters, presentations, invited reviews, etc), unlimited page length, professors can have upwards of 40 pages
These days most people also have a LinkedIn profile which is expected to be complete. Holes in the timeline may raise questions.
These days employers use bots to process hundreds of CVs in one go. One anon notes:
It is important to understand why bullet points are important. Resume bots are looking for keywords and you want to jam them up to the maximum density you can in your resume.
Anons report on difficulties in getting a letter of recommendation, especially in academia. One noted with particular brutality:
Unlike corporate jobs, which require people who manage other people to focus on management skills, academia promotes people to management (PI) positions based on how much money they bring in (grant indirects) which is a function of luck and scientific autism, which itself is negatively correlated with good management skills. This means that the system is full of survivorship bias retards who think supervising = yelling at people because it worked for their particular situation.
And another added:
also remember that industry pays better in money, while academia pays people in ego strokes, good boy points, and fancy titles. This attracts certain kinds of people, obviously. Naive idealists at best and psychotic narcissists at worst.
Some professors keep their students and postdocs hostage to further their own career. One way around this is to ask for a letter of recommendations at a point when the professor has no hold over you, for instance when your funding is coming to an end and the professor cannot hold onto you any longer. Some professors try to delay their students to use them as cheap labour in their labs and should be avoided.
So, armed with your CV/resume, you start checking out the job openings, be it in academia, national labs or industry. There are a few things to keep in mind when you read about the job openings. Many have a lot of requirements, sometimes set by HR with little understanding of the matter. This means that even if you don't have a 100 percent match, you can still apply. After all, if it is too detailed, how many applicants will they get? The second point is the inverse of this: excessively specific job openings, where perhaps only the shoe size is missing. These are meant for a person already working there but they just have to go through the motions with posting something, so they start with the CV of the person they are already planning to give the job to. From the discussions:
>True. If you ever run across a job opening for a PhD and the description seems super specific, it's because they already have someone picked out for the job and the posting is an HR formality. They'll even use the guys resume to build the job posting.
That happened to me. I had everything they asked for, including the "preferably a PhD" part. I got an interview but since I was naive I couldn't understand why the interview dragged on for hours and hours. I was even more mystified noticing that every time I could confirm I had a particular experience, the interviewer looked even more pained.
Of course I didn't get the job. I called and asked, got no clear answer, but was asked if I could take on this as a short term contract as the person who got the job would be delayed. I said yes. And being naive I didn't really ask much about the person who got the job or why this person was never mentioned. I was just doing my job and found it more interesting than the strange politics.
That is, until one day when it just plopped out from one member of staff that the person who got the job was one of the students in the group, who was "delayed" since he was still writing up his PhD thesis. I am no longer naive and I am of course not working there.
In many ways the experience is that if you didn't get the jobs
because of crazy manoeuvres, you probably would not like to work
Another major problem are all the fake job ads. People put out
fake jobs, at times even
fabricate the entire workplace, for all sorts of reasons.
Some times it is all about keeping up appearances, especially
when competitors are posting lots of job ads, other times it is
just used as a way to cheaply advertise for the company. Even
experienced people fall for this, or so your editor insists
since I also fell for this. One anon summarised what to look out
So you get a position. Well done. And now starts the politics. The nature differs from academia to industry and there are also a lot of variations within each. People tend to call this "culture," presumably people who get their main cultural intake from yoghurt. It is very easy to veer into doomer terrain here, but a few issues should nevertheless be kept in mind.
Promotions do not necessarily follow from competence, networking trumps competence. So be visible in your organisation and keep your LinkedIn profile up to date with your company.
Read up on organisational theory. You will find a lot of strange psychological musings but also a lot of explanations why things are the way they are, even if it is plainly insane. Keep records, with backups, to protect yourself when the blame game starts.
When you leave, be it moving to a new job or losing your job in office politics, resist the epic nuclear approach to leaving, and keep the moral high ground instead. Fate tends to catch up with everyone. If you sit by the river long enough, you will see the body of your enemy floating by.
This is a hot topic in the sense that people have very strong opinions about it, though not always fully informed. There are a few things scientists should know about this.
First of all IPR can be divided into two kinds: registered rights (patents, trademarks, and design (called "design patent" in the US)) and non-registered rights such as trade secrets and know-how. There are important territorial differences and laws, so there are many exceptions. Copyright is a registered right in the US but non-registered in much of Europe. What is important here is that your university and your employers will most likely have IPR related clauses in your contract. These are boring but important, do read these carefully. Also check the scope, such as how far after termination of employment the clauses will reach. Surprisingly many employers try overreaching what is reasonable, so be careful what you sign.
New inventions tend to be kept as trade secrets until the HIPPO (highest paid person in the office) decides if it will be protected as a patent or kept secret. A secret is an all-or-nothing approach: very effective in many cases and can last decades, but will implode the day someone spills the beans. This person will be sued out of the window. Make sure that is not you.
A patent lasts typically up to 20 years but will be published. If you are a (co-)inventor you have certain rights to be named (if you wish, for spicier inventions such as sex toys inventors will use their right not to be named) and quite possibly compensation. Most likely the contract will have clauses giving your employer the rights to the invention. You can list patents and patent applications on LinkedIn, and one anon wrote that one patent is worth 10 publications.
Since patent applications are published and carefully classified, you can use patent statistics to see if a specific field is hot in academia and/or industry. For this you can use free patent databases with specialised search engines such as Patentscope. So to take two examples from an earlier discussion:
Nanotechnology: Use Simple Search, enter "nano technology" into the search box, hit enter. When the result appears, click the graph/curve symbol in the upper right hand side to get full analytics. From this we see over 63000 publications with an uneven growth to about 10,000 publications annually. Some important caveats: these are publications, typically 18 months after first filing date, and can be patents or (typically mostly) patent applications, so there are many filed but as yet unpublished applications. Also this searches for the text in the application itself.
Quantum communications: Time to step up the game and use classification search. Patent Examiners will classify all incoming applications according to carefully worked out standards. This means that an application that doesn't use the exact terminology will still be found in later searches. So we start with finding the right class. Go to the IPC (International Patent Classification) page, select "Search" near the top, enter "quantum communications", and click search. The brings up a cryptic list of letters and digits. We try the first and presumably most relevant, "H04B 10/70". And indeed this is a really good hit. Copy this code and now try search with Field Combinations. Select the second line middle pull-down and select "International Class", enter "H04B10/70" without space, hit enter. Again click the graph/curve symbol in the upper right hand side to get full analytics. From this we see over 2100 publications with an uneven growth to about 400 publications annually.
You have to experiment to get a good search, it takes experience and there are pitfalls. For instance using "nano technology" catches far more than "nanotechnology", yet searching by the appropriate class "B82" brings up about 110,000 publications. You can also search for employer or university, search for applications by your PI and more. If it gets too complex you could also ask in the general, since there are several anons familiar with the patent system.
One anon noted that
Read up on rhetoric, it is a skill that goes more than 2000 years back. I had a very short course in this and it has been very valuable. Technical guys need this more than most since we tend to believe being technically correct is all it takes. Outside Simpson jokes, it is not the case. Emotions trumps facts, the extreme example being Challenger launched against the strong recommendations not to launch voiced by the scientists and engineers. Shuttle launched, exploded, killing all astronauts, major destruction of government property, space programme broken for years: management was never even prosecuted.
Rhetoric is simply put the skills needed to persuade others or make them see your point. This skill is valued in politics, management and law, emphasising pathos, while technical guys tend to focus on logos alone.
Getting relevant internships is increasingly important for a good career. It gives experience and lets you build your network. Some recommend getting at least two internships before graduation.
In the US you have GS (Government Service) internships, which is a huge advantage, because, in the words of an anon "you are in the federal government you are IN and you have pretty unique opportunities to move around laterally to different positions. The downside is that you need to apply 6-12 months in advance because the government works at random speeds." It was also noted that "on a scale of 1-15. Most STEM types are brought on at grade 9 right out of college and auto-promoted year over year till they hit GS-11. This is distinct and different than being a contractor who the government has hired. GS positions are notable for being one of the few jobs out there that still has a pension and the type of work available to you can be…esoteric to say the least."
Several anons report that they get "accepted" into internships, but things are not quite what they seem:
What's also strange is that after finishing the questionnaire you're told, "We will be in contact with you if you're selected" even though the recruiter I talked with spoke as if I'd already been accepted. Now I'm waiting here to receive a response and wondering if this was another part of the filtering process. It would feel pretty silly if so.
Anons report this has happened both in the US and Europe. Don't fall into this trap, the reason is ugly:
I think recruiters often do that to try to nail people down (discourage applying for more) because they lose nothing if the position falls through.
So when you get "accepted", keep applying for more so that you too have a fall-back position. And remember your position could always disappear overnight.
Let us not forget the comics!
Piled Higher and Deeper, life as a PhD student
Antimatter Webcomics – Annihilating matter since 0.2 milliseconds after the Big Bang.
Microscope – "a webcomic on science, academia, research,
and other stuff. Come and have a laugh (or cry) about the ups
and downs and absurdities of the "labrat" life" according to the
In addition to comics, we have fun videos such as Tom
Lehrer on plagiarizing.
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