The degree of success one can achieve in any environment, specifically a lab, depends upon appropriately matching individual talents with an environment. There are many web resources that describe how to succeed in graduate school, or in a job [in a subsequent update to this post, I’ll include links to my favorite ones]. Here, we try to list the qualities of individuals that we believe tend to be positively related to “success” in our lab. We believe these qualities are also likely to be positively related to success in other positions, but are relatively data poor for the other positions. On the other hand, we’ve interacted with between 50-100 individuals so far, and have therefore amassed a fair bit of anecdotal evidence.
- Mission Aligned Our mission is to
Understand and improve animal and machine intelligences worldwide. If you are motivated to solve these problems, over and above any other problems, you are in the right place. Read our mission for more details.
- Interest in Data Science Our work is at the intersection of statistical machine learning, brain science, and mental health. If you are maximally intrinsically motivated to study this intersection to achieve our mission, read on.
- Personality Traits Each institution/lab is a unique environment, with unique quirks, ours included. The traits that seem most important to us include:
- enthusiasm for solving these problems;
- humility to realize that we are all often wrong, and the goal is to learn and understand, rather than be “correct”;
- gratitude, both for the opportunity for learning and growth that comes from our errors, and because we get to work in the best environment with the best in the world;
- patience, because these things are hard and take time;
- simplicity, because the fewer parts the easier to understand and the less that can go wrong; and
- trust in each other, as each member of the team has unique talents.
- Data Science Chops To succeed, you’ll essentially need to learn or already know graduate level probability, statistics, matrix analysis, network science, and some numerical programming and brain science. If you plan on developing methods, strong numerical programming skills are required. If you plan on applying methods, strong brain science understanding is required. If you plan on proving theorems, more theory is required
- Technical Communication Something that is particularly difficult to quantify, but as important as the above properties, is an ability to communicate technical content to us effectively. This is important because we work on teams, and the efficiency of our team is partially determined by our ability to communicate effectively with one another. We acknowledge that this is highly subjective, a given individual might be able to communicate effectively with some people, and not others. This does not require fluency in English per se, but does require being able to speak, make slides, and write reports about technical content in a coherent fashion. This is something we all learn by doing, it is not expected that anybody joins the team knowing these things.
- Agreements Our team made a set of agreements, that we continue to update as appropriate. Agreeing to these agreements is a prerequisite to joining the team, and therefore, is required for succeeding on the team. If you have recommendations for how to further improve our agreements, please let us know. Note that these agreements include both personal and professional activities.
- Learn Context To make a meaningful contribution to the literature, it is helpful to know what is already known in the literature, and what are the biggest feasible open challenges. There are many kinds of activities that help you gain context including:
- Take relevant classes. We specifically recommend classes taught by Jovo, Carey Priebe, Randal Burns, Rene Vidal, and Raman Arora.
- Attend conferences. One to two conferences a year, for example, one large general conference and one smaller specialized conference, can be invaluable for learning. At those conferences, literally attend all possible conference activities, including all talks, posters, social activities, and workshops. For multi-track conferences, as long as one track has an activity, go to it. Expect to be learning essentially 12 hours a day. Take breaks as appropriate, probably nearly hourly, to decompress. It helps to attend talks/posters/etc. with other people who are more senior, so that you can discuss the contents afterwards and digest the most important points. Go a day early, or stay a day late, to be able to enjoy the city you are in; there is no need to do those activities during the conference, there is plenty of time after. If at all possible, do the fun activities with other conference attendees, ideally not from your lab.
- Read papers. There is no limit to the number of papers one can read. If you find a really interesting article, read all the references of that paper. A good rule is read an average of one paper a day. The depth with which you read it can vary as appropriately, from only 30 minutes to get the gist, to 8 hours to understand the details. If you think you want to read a paper for 8 hours, first read it for 30 minutes, and then read the key references each for 30 minutes. Then do the 8 hour read.
- Plan on Being Here a While Many people approach us and are interested for a summer internship, or even a year long fellowship. It is quite difficult to make a positive contribution in less than 1 year, for the simple reason that there is a lot of specific background knowledge and context that the lab has that is nearly impossible to get anywhere else (this is likely true for most labs). PhD’s take about 5 years, that is long enough to be able to make a contribution. Realistically, after about two years, expect to make a useful contribution, that is, your research output more than exceeds the output the team would have had had you not been there (which means you’ve overcome the research debt accrued by virtue of the energy spent training you). The efficiency with which you can make contributions continues to increase with training. Ideally, the best trainees would never leave, meaning, they would either take a postdoc position with us, and/or get a faculty position at JHU, or a neighboring university if that makes more sense for various reasons.
- Meet the Experts There are many brilliant people working on related questions all over the world. To the extent possible, meet them. I know of three ways:
- Sign up for relevant seminars and attend them. At JHU, this includes the following seminar: CIS, data, CS, BME, CS theory, AMS. Please email us if we forgot any. At the seminars, if you don’t understand something, raise your hand and ask a question. The speaker’s job is to make you understand, either during the talk, or if they deem it appropriate, after the talk. Let them choose when to answer, rather than choosing for them. Also, when possible, sign up to speak with the speakers. For many speakers there are lunches with students, go to as many of them as you can. If there is no lunch, either sign-up to speak with them yourself, or with a small team of other students, or ask your PI to join their meeting.
- At conferences. Prior to the conference, say about 1 week before, find out which faculty that interest you will be at the conference (if they are speaking, they will be there). Email them all, offer to meet them at literally any time and place that is convenient for them. Offer to meet them at the airport, or go with them to the airport, if necessary. Faculty tend to love this kind of thing, as it caters to our egos. Also, it makes the rides more enjoyable. After their talk, go up to them and ask them questions, or simply tell them how much you learned and how much you appreciate their work. Don’t forget to introduce yourself, and in 30 seconds, tell them whose lab you are in, and what your main project is focused on.
- Invite faculty of interest to seminars. In many seminars there are slots for student invites. In others, faculty decide, but should always be willing/interested in inviting faculty that are interesting to the students. So, bring the faculty you want to you, and then be their host for the day, take them around to their meetings, join them for lunch and dinner, etc.
I imagine there are other qualities that I’ve forgotten. If so, please let us know in the comments below, and we can update this list.