PhD and working in the industry

Working in the industry provides an excellent opportunity to apply your hard-earned research and technical skills in practice towards developing products/services of value. You get to work in a relatively polished and systematic work environment where the nature of work changes as the competitive business landscape changes. You get to work with top talent in your field in a diverse work culture spanning geographical areas (and even continents) towards a common goal of delivering a high-value product/service to your customers/clients. Due to the length and breadth of technologies involved, there is reasonable freedom to choose a role you enjoy and are good at. As you develop more skills in your work, you earn more autonomy.

Any role in the industry would involve a combination of the following.

  1. Product development
    Depending on your industry and role, it will involve one or multiple of the following: running experiments, data analysis, software/hardware development, testing, validation, process engineering. This would take the bulk of your time and essentially justifies your addition to your company’s headcount.
  2. Background research / skill development
    Understand the state-of-the-art, hot topics, pressing problems, limitations of the state-of-the-art, verifying, and validating your methodology and approach with the literature. Develop new technical skills for your current/new role as needed.
  3. Developing intellectual property
    Develop methods/algorithms/techniques to solve a pressing technical problem. Occasionally file patent applications on some of those.
  4. Publications and conferences
    Writing white papers, research papers, and participate in industry/research conferences in your field.
  5. Contribute to the standards bodies (such as IEEE, ISO, ITU, etc.)
    Influence the technical direction of your discipline and represent your company.

In the early years of your career, you are expected to spend a significant % of time on (1) and (2) and get your feet into the ground. As you mature and move up the corporate ladder, it will be spending more time doing (3) to (5), however, nothing stops you from doing it in the early years as well.

The bulk of the technical headcount in any company works on the product-development side of it. Some companies have a separate research division (aka research labs) with max. 5-10 % of the total headcount. However, those divisions are an increasingly smaller share of the company’s headcount (think IBM Research) [1] or have nearly vanished (think AT&T Bell Labs). Moreover, many new-age technology companies (like Google, Facebook) have almost done away with that structure [2].

Often, Ph.D. students are under the impression that they only belong to the company’s research side. However, that is increasingly less common, especially in the computer technology industry [2]. Between a role in the product-development side and the research side, the main difference is the % of time spent in the above five activities. Also, over the course of your career, you could be moving between product-development and research roles. Rather than obsessing over whether to work in the industry or a research lab, it’s better to focus on the specific skills you need to master to succeed in your career.

To succeed in the industry, we need to find the right fit for our skills and abilities. In our Ph.D. process, we spend a significant amount of time/energy developing certain skills relevant to a specific domain. As we start looking for jobs in the industry, we might realize that the domain and/or the skills are not as relevant for the market. So how do we go about finding the right fit? One exercise I find useful is to identify the knowledge domain and technical skills for a job opening. By domain, I mean the knowledge area of your research. By skills, I mean the specific tools/techniques/methods that you have mastered in your research area so far. Let’s consider an example. Suppose your research is in applying machine-learning techniques identifying tumors in medical images. Then your domain is medical imaging, and your skills are machine-learning (ML) techniques.

As you are looking at the job openings, identify the specific domain, and skillset it requires. Same way, identify the domain and skillset of your research experience. Ideally, going from one position to another (Ph.D. -> PostDoc or Ph.D. -> industry or PostDoc -> PostDoc), try to change either the domain or the skill. This helps in having a solid grounding in one while picking up the other. How about applying ML techniques to identify objects for self-driving cars or learn new statistical techniques (say deep learning) in the medical image domain.

References
[1] https://cacm.acm.org/magazines/2015/1/181626-the-rise-and-fall-of-industrial-research-labs/fulltext
[2] http://academicsfreedom.blogspot.com/2012/08/advice-for-phd-students-seeking.html

Postdoc and Productivity

Last updated – July 19, 2020.

Disclaimer: I have never worked as a PostDoc myself. I am currently mentoring a close friend who is pursuing a PostDoc position in Israel after graduating with a Ph.D. from India, which motivated me to write this blog. Also, I worked closely with several Postdocs during my grad. school, which has shaped my experience and thoughts.

Pursing a Postdoc position is an excellent opportunity to pickup new technical skills, venture in a new technical domain, expand your network, and work in a different environment. However, just like the PhD program, it is reasonably unstructured, and your experience can vary significantly by the lab, advisor, and timings in general. Unlike the PhD program, the end goal is not as clear. This calls for a fresh thinking in your strategies to set meaningful goals and manage your productivity towards it. I summarize my thoughts here.

Goal Setting

A PostDoc position is a intermediate opportunity towards a more stable position in the near future. One needs to gain competence in many areas (research, teaching/mentoring, networking) in a relatively short span of time. However, everyone comes with a different level of competence and exposure in each area. One needs to set their own goals and prepare for the next position. In addition to the traditional techniques like SWOT analysis, here are some of my tips to help set your goals and expectations.

a) Write/edit your research/teaching statement regularly
One of the outcome of your postdoc experience is a crisp and solid research and teaching statements. Such documents provides a holistic picture about your past and present experience, and your next goal in career. Rather than writing the statement at the end of your position or when you are applying for a new role, it will be great to write it regularly. This will help you identify gaps and potential areas of improvement. It will be great to share this document with your advisor and colleagues regularly to seek their feedback. This will help them coach you better.

b) Recommendation letter
By now, you would have realized you will be drafting most of your recommendation letters yourself! Why not use this as a goal setting tool? In addition to your statements and publications/projects, solid recommendation letters can have an enormous impact on the hiring decisions.

c) Job Market
Try to peek into the job market every quarter or so, to see what skills are being talked about, the domains that are picking up steam and so on. Use this information to steer your projects in a direction that will help you pick up those skills/domain, while still meeting your existing projects/funding requirements and your advisor’s expectations. I plan to share more thoughts here in a future blog.

Productivity

a) Work like a professional
In a PostDoc position, people around you (lab colleagues, Advisor, funding agencies, collaborators etc.) expect you to work like a professional. This should reflect in your communication, your lifestyle, your maturity and so on. Practice working limited hours. Value your time in terms of $/hour and judge if a task is worth your time, otherwise delegate to a junior who would benefit from that learning. Set the expectations with your colleagues and practice delivering on time. This is the minimal expectation from a Postdoc graduate, whether you land up working in academia or industry after this.

b) Schedule regular meetings with stakeholders
Stakeholders includes your advisor, colleagues (junior or peer), funding agencies. Schedule meetings with an appropriate frequency (like weekly with advisor and colleagues, biweekly or monthly with funding agencies and so on). Share updates, challenges encountered, and keep in-sync.

Also schedule regular meetings with your mentors, discussing your career progress, lessons learnt, etc. Regular meetings will keep you keep your eyes on a big picture. Do the same with your mentees.

c) Health and well-being
I bet you weren’t expecting this as a productivity tip. This is key to the long-term career success, and in many cases, the learning starts only once you are “over” with the college lifestyle. Very likely, you have moved to a different location or even a new country for your postdoc position, resulting in significant changes in your lifestyle. Spend time to cope up with it, whether its furnishing your new home, picking up a new hobby, socializing with your new friends and so on. Check if the weather of your new location can affect your health, like possible Vitamin D deficiency in cold places.

Applying for Ph.D. programs in the US

I recently graduated with a Ph.D. in Computer Engineering at Duke University, NC. Before that, I earned an M.S. degree in Electrical Engineering from the University of Southern California (USC), CA in 2010. Based on my experience while applying and during the program, I would like to share my thoughts here. I am sure there are plenty of books and other resources for this information, and I hope the information in this post compliments that information.

Application process

Most universities have application deadlines around December for admissions for Fall semester (starting Aug/Sep). Some universities also have application deadlines around September, for programs beginning Spring semester (Jan.). Check with the university/department for exact dates and other details. Keep in mind that a majority of students would join in the Fall. But that shouldn’t hesitate applying for Spring term, if it is working out well. The application package usually consists of

  1. Research Statement
  2. 3-4 recommendation letters
  3. CV and related details
  4. Application fee ($$$)

Research Statement

I referred to this book while preparing my statement. It provided some solid examples of what the committee is looking for, what part of your profile to highlight and so on. Approach this task with an open mind. Get initial drafts done and then share it with your current Advisors, friends etc. for feedback. Avoid plagiarizing parts from others essays. Depending on your research depth in the field you are applying for, you can get more technical or keep it a bit high-level. If you are having trouble getting your words down, consider practicing techniques from this book. Be prepared to customize the research statement for the program/lab you are applying for (more hints below).

Recommendation Letters

Some recommenders are happy to write the full letter by themselves (and keep it confidential as well :0 ), while some expect a rough draft from you before they polish it. Either way, make sure that you share with them all the possible points they can write about you, like the cool class project you worked on, the research project where your contribution made the difference and so on. Please encourage your recommender to share their personal experience of working with you, whether you demonstrated leadership experience, mentored a junior student, volunteered for tasks and so on.

Timeline wise I would prioritize sending requests / rough drafts of letters to your recommenders over all other activities of the application process. Professors are busy during the semesters. Plan to have a buffer of a month or so before you start nudging them. Consider having a backup recommender as well, in case one of the recommenders forgets to turn in the letter on time or is particularly busy around the application deadline period.

Application fee

If you are applying from outside of the US, you might find the application fee quite steep. However, keep the long-term perspective in mind. Recovering the application fee will take a trivial amount of time once you get into the program, or later in your career. However, refrain from applying for programs where no faculty has shown interest in working with you, or you wouldn’t be as keen on studying there even if you get admission (some call it “safe schools”). Consider getting a credit card that reduces unnecessary foreign transaction fees

Finding the right match

Academic factors

  • Advisor’s working style – hands-on vs. hands off. And how it changes through the course of the program
  • Lab culture – do students collaborate with others or work independently on projects? Is there a group meeting or everyone meets advisor 1-on-1?
  • Lab organization – How many students are there? Is there a PostDoc in the group? What is the typical duration of Ph.D. students and PostDoc? Do PostDocs mentor Ph.D. students? How are mentorship responsibilities divided between Professor (also called Principal Investigator (PI)) and PostDocs? Do senior Ph.D. students mentor junior students?
  • Grants – Hows the funding scene in the lab overall. Are current students facing difficulty getting a continuous stream of funding? Did a student leave the group for lack of funding?

Non-academic, but reasonably important factors

  • Location: Big city vs. mid-size city vs. university town. Big cities provide broader access to the real-world and opportunities but come with additional cost and distraction. University towns offer limited amenities, but students in the university town tend to bond better as a group. Mid-size cities provide something in between the extremes. Cities in the US are not as walkable as those in Europe or Asia, so you might want to have a car in the later years of the program.
  • Weather and seasons: Severity of winters, rainy or dry. Depending on which part of the world you come from and how fast you can get used to the weather — also its impact on your physical and mental health and well-being.
  • Proximity to family and friends: Ph.D. programs are long and can take a toll on your mental health. It is worth-a-while to stay in touch with your family and friends, whether its occasional phone calls or impromptu weekend trips or planned trips for Thanksgiving or Christmas. Also the convenience of traveling back home.

Finding potential advisors

There are many universities around the US and many professors within each University that could potentially work with. So how do you go about finding a great advisor and an excellent research lab? I have several approaches in mind

  1. Ask your current advisors to see if they know advisors who might be looking for students or whose research interests seem to catch their attention. Professors network with others during conferences and working groups and are reasonably aware of the activity level and quality in other groups around the world. This approach is possibly the best approach to find the advisor since you get a first-hand recommendation of both the technical and interpersonal quality of your advisor to be. This approach is a feasible option if you are finishing your Master’s degree and your university advisors are still accessible. However, if you have graduated already, and/or looking for researchers in a different research area, you might be your own.
  2. Reach out to potential advisors yourself. Professors love to hear from folks who are excited about their research and are interested in working with them, so never hesitate in reaching out to them. There are several ways to find out folks who are working in areas of interest. I find technical magazines (such as IEEE Computer in my field) the best resource to start with. Articles here are published in research areas which are hot and exciting and written by folks who have breakthrough results to share with (read -they have or will soon have $$$). If you find an article interesting, think about ways to extend the research. Are there potential assumptions that need to be revisited? Has the research been done in one kind of system that can be done on another system? If you have ideas or comments worth sharing, reach out to the authors. Try to strike a conversation (more details in next section)
  3. Meet them in a conference, seminar or a similar setting. If you are presenting a paper (on your master’s thesis or otherwise) in a conference, actively network around with other participants. Ask what are they working on. Share with them what you are working on, and what opportunities you are looking for. Be upfront and courteous to ask them if they are aware of open positions and possibilities. Researchers are usually excited about such conversations and can offer you great leads.
  4. Attend conferences as a student member. Even if you don’t have a paper to present, conferences almost always allow students to participate in conferences, at a pretty discounted registration fee. You can also consider volunteering for the conference to get some discount. Again, researchers are always looking for new students and happy to share their network as needed. They would look for someone who is excited about their research area, is ready to learn and work hard, and good at communicating and working in a social setting.

Getting in touch with potential advisors via emails

In your email, describe your research interests, current research tasks, and potential future goals and how it relates to the Professors’ work. Keep your emails short and to-the-point. Extra details can go on your website or LinkedIn profile, and you can add a link in the email. Avoid attachments. Your first email should be 1-2 paragraphs max. with total 6-10 lines. So you should be able to summarize your research statement in a few lines, and connect with their work and create the bridge. It should sound like a win-win situation, but you don’t have to try too hard to do it.

Note that if a Professors doesn’t reply, it does not mean he/she didn’t read the email. So it is possible that you apply to their university, and he/she will recall your email after picking up your application. So never lose hope. However, If they explicitly reply that they are not hiring, then you should move on.

If a Professor expresses intent, immediately add relevant points to your research statement. Keep polishing the statement as the conversation goes further along. Also take notes on points that you would like your current Adviser to talk about in the recommendation letter, so that can strengthen specific aspects of your statement.

University Rankings, reputation and related discussion

Never think that some program/lab is too high for you to reach, or it’s too low for your profile. If you have the right intention, everything works out. Given the amount of “data” we are surrounded by, it is easy to get obsessed with the rankings, ratings, and reputation of universities and departments. However, keep in mind that your success in the Ph.D. program largely depends on your motivation, your relationship with your advisor and other collaborators and to some extent luck and destiny in getting the right projects and timings. 5 or 10 years after graduation, you will remember the opportunities you received and the relationships you developed, not the rankings of the lab/university you worked in. Besides, it is hard to rank research opportunities. Universities/departments are usually ranked by the $$$ they attracted in research grants, which is hardly reflective of the student’s experience working there. Rather than getting obsessed with the rankings, have a broader perspective in mind.

Once you receive an admit from a university, they usually invite you for a campus visit, sometime around Feb / March. Even if you are outside of the US, I would highly recommend you to go there. The university would cover your stay and travel within the US. You can interact with your potential Ph.D. advisor(s), students, and other faculty and staff in the department. Also, meet the fellow students who plan to join the department as well. After interacting with folks there, you can take a better decision whether the place is a right fit for you.

Funding

Ph.D. programs in the engineering disciplines in the US are almost always fully funded. Full funding means tuition fees, health insurance, and stipend. The stipend amount varies across universities, but it is typically in the range of $2000 per month. In some state/public universities, you might need to pay a small tuition fee, around $1000 per semester. In summary, you will be spending only a small sum of money out of the pocket during your program.

In the US, usually, the advisor is responsible for the full funding of the student. Which indirectly means that you are his employee and he/she is your boss. Some departments cover the first one or two years of funding. However, you can always apply for fellowships from within the university or outside. Outside fellowships can come from government-sponsored research labs (such as NSF, NIH, Department of Energy) or private corporations such as IBM, Intel, Microsoft. Unfortunately, only US citizens can apply for government-sponsored research fellowships. University fellowships are usually open to all students, and all years of the program, however, they tend to be competitive. Your advisor and the department will help you prepare your application for the same. When you apply for a Ph.D. program, your application is usually considered for university-sponsored fellowships automatically, or your advisor can push your case when you are an incoming student.

When your admission letter says that your funding is covered, it means that the department will cover your funding in case your advisor falls short, conditional that you are in good standing and making progress on your program. Although your advisor promises that he/she is funding you, it does not mean he/she has 5-6 yrs worth of your expenditure sitting in an account. It means your advisor (+ department) has funding to get you started, and he/she is hopeful that they will be able to find funding for you in the future. Given the uncertainties in academic funding, it is a tough task for an advisor. As a Ph.D. student, you are expected to work with your advisor to help him apply for grants for your lab. Also keep an eye open for outside funding (e.g., industry internship), whenever it aligns well with your research interest and can take some burden off your advisor’s shoulders.

Contrast between European and US Ph.D. programs

Application

My limited knowledge about the Ph.D. programs in Europe is shaped from a summer internship in Zurich and my interaction with visitors from various EU countries in our lab, so pardon me in advance. Here’s how I look at it. A Ph.D. program in Europe is treated like a time-bound research project with reasonably well-defined goals and objectives. A Ph.D. program in the US is treated more like an experience of maturing as a researcher, which includes teaching experience, handling research projects with varying level of responsibilities from being an assistant to a senior in your lab to being the project leader, identifying thesis-worthy topics, seeking out collaborators to work with and so on. Thus, applying for a Ph.D. program in Europe is like finding a job position, whereas applying for one in the US is like finding a match (like a relationship). Given the number of variables and its uncertainties in an American Ph.D. program, the experience can significantly vary among students even within the same research lab. A friend of mine once told me, “Every Ph.D. thesis is unique.” Thus, it is worth spending the time and energy to research the advisor, the lab, and the university/department culture to find the right match

Work experience

I would refrain from generalizing my observations here. But given how often I have seen this pattern, I wouldn’t outright ignore it. I feel the students in European style Ph.D. programs are expected to master a skill (think of experimental work vs. data collection vs. data analysis vs.…) and get involved in all projects (and publications) in their lab that require that skill. So the first author on the paper is responsible for framing the problem and get pieces solved by colleagues who are masters at it. In a US-style Ph.D. program, the first author is expected to be good at most of the skills required on the paper, and involve colleagues and collaborators only as needed. The result is a difference in the breadth and depth of skills you acquire and polish over time. I see enough counterexamples as well, where Professors of European origin continue their style of work in the US and the other way round. The takeaway here is that if you are coming from one form of learning, be prepared to unlearn and adapt to the new style when you cross over the Atlantic. In case you experience difficulties, never hesitate to bring this up with your PI. They probably understand it better.