THE GROUP

Overview

Our group utilizes theory, simulation, and machine learning to understand and design chemical/materials systems. We are particularly intrigued by polymer-based materials with implications for health, sustainability, or consumer applications. Within this large space, we pursue projects that are identifably important or interesting to society but can be specifically advanced by the group’s expertise and capabilities. We engage in a combination of fundamental mechanistic inquiry (i.e., understanding why things are the way they are), targeted design (i.e., finding something specifically good for a given task), and methods development (i.e., improving or innovating on current approaches to enable new science). The balance of these may vary from project to project. In all cases, we aim for research that is highly rigorous, well formulated, clear, creative, and honest.

What kind of theory and simulation?

Our group engages in multiscale simulation and theory. The range of spatiotemporal scales encountered in the group extends from single small molecules up to around maybe 1000’s of microns and microseconds. The most common flavor is classical molecular dynamics or closely related approaches intended for extended spatiotemporal scales (e.g., Langevin dynamics, dissipative particle dynamics, multiparticle collision dynamics). You may see that we typically use particle-based methods versus continuum approaches, as the former is more within the group’s expertise. We will also use Monte Carlo or kinetic Monte Carlo techniques where appropriate. Some projects may conduct quantum chemical calculations (e.g., for molecular characterization or force-field development), but we are not electronic structure theorists. Statistical mechanics and polymer physics are very important theoretical frameworks for our research. We are also keen to draw on other literature bases (e.g., network analysis, graph theory, machine learning) for mathematical guidance or inspiration for our own pursuits.

Beyond the broad classifications just proferred, I would highlight specific interest in and use of

  • bottom-up coarse-graining methods

  • path-integral techniques (for treatment of nuclear quantum effects)

  • enhanced sampling approaches/free energy methods

Why polymers?

Polymers are not the only class of materials that we study, but they are at least heavily featured in the group. Why?

First, I am overall fascinated by the potential of polymeric materials to be used across so many different applications. As a design construct, in principle, we can manipulate properties and functionality of polymeric properties by changing

  • the chemistry of constitutional units

  • the sequence/composition of units

  • the architecture of the chain/system

  • the environmental conditions

  • and more…

Second, the properties of polymers/soft materials can be unintuitive. Relatively small changes in chemistry and result in drastic effects. That does not necessarily mean we cannot offer reasonable hypotheses, but there is a lot that remains unknown or unclear about why certain polymer systems behave the way they do. This provides an interesting and challenging starting point for study. It also serves as a partial justification for the role of simulation/computation in facilitating predictions.

Third, interesting properties and behavior of polymers/soft materials often arise due to their multiscale nature. As a consequence, their very description often requires the type of coarse-graining or enhanced sampling techniques that we deploy. In fact, such techniques are often motivated by the purpose to study polymers or other soft materials. If you have simple small molecules – you could coarse-grain them and perform extremely large and long simulations, but should you? Most of the physical properties of such systems can be understood from relatively small and short simulations (e.g., 3 nm \(\times\) 3 nm \(\times\) 3 nm for 10 ns); we don’t need huge, long simulations. To describe polymeric materials, we may, in fact, have this need.

In summary, they are interesting and technologically relevant systems for which there is a clear need and reason to study using multiscale computational techniques.

What about machine learning?

Increasingly, we are interested in exploiting techniques from the realm of data science to enhance our research efforts. This is a growing trend across physical science and engineering, and it has truly transormed the way that we approach science. I do not favor its application without intent/purpose. It is not the first solution to all problems, but I am optimistic and enthusiastic about what it can enable. I am most interested in applications of machine learning for soft materials and multiscale simulation. Advancing research involving polymers and polymer design with machine learning is a niche that we have fit into well over the years. Machine learning is also a very valuable tool for analyzing molecular simulations. There is a lot of fantastic work involving machine learning in chemistry and other materials contexts. Based on my own background, I have less to intellectually contribute to that general arena, but these developments can be great sources for inspiration.

Will I like computational research?

I hope so. If you are an undergraduate, this is a great, low-risk time to experience computational research and assess compatibility (particularly if this is a summer or semester thing… a senior thesis is a more substantial investment). Speaking from experience, my engagement with molecular simulation as an undergraduate was genuinely life-changing (or life-determining?). Many folks pursuing a Ph.D may have exposure to computation/molecular simulation and a sense that they like it. At that point, the question is more compatibility with the group culture, advising, and research areas. Postdoctoral researchers should have clear intent in their selection of postdoc destinations and are most likely nominally in the field or adjacent.

The trickier bit is when someone has no prior experience with molecular simulation, and I often get the question as to whether one can do research in the group without having had prior experience. I can assure you that this is not a problem. Let me critique the idea. First, it is always necessary to have had no prior experience (at some point), so not having done a thing does not discount the ability to do it in the future. Second, while it is perfectly fair to wonder whether , I would speculate that a large number of Ph.D candidates had no prior experience in the specific experimental methods encountered in experimental groups. So, it seems a little unfair that computation gets singled out. Nevertheless, a Ph.D is a serious commitment, so it is good to have some leads.

Here are what I consider some likely indicators (not requirements) that computational research and my group might be “right” for you.

  • You enjoy coding/programming/debugging. This is our bread-and-butter and day-to-day. Here is good advice that was given to me once (I believe from my own Ph.D advisor, prior to joining his group): if possible, it’s best to pursue something if you can enjoy the most mundane or rudimentary task associated with that pursuit. For us, I think that is banging out scripts in a terminal and figuring out how to make things work. My first real exposure to programming was in undergrad (I realize programming skews way, way younger these days), and the logic and flow really resonated with me. After my undergrad research experience with molecular simulation, I was totally sold. You don’t need to be there, but if you have hated your experience with programming, then it might be good to consider something else. Even if the research sounds cool, it’s hard to sustain yourself on this grand vision when you are confronted with an insidious bug.

  • Your favorite classes may include physics, thermodynamics, statistical mechanics, or physical chemistry. These topic areas provide the foundation for molecular simulation and its various applications. So, research in the group is often strongly tied to these areas.

  • You like control/optimization/math.

Logistics and Operation

Office Spaces/Common Areas

All of our spaces are located in E-quad. Please do what you can to ensure that common spaces are neat and clean/hygienic. If you make a mess, clean it. Do not leave junk scattered all around.

  • A325 - Prof. Webb’s Office

  • A326 - Group space 1 is located across the hall from Prof. Webb’s office. There are six desks and a common table. There is also a microwave and mini refrigerator. We have thankfully not had any “refrigerator stories” – let’s keep it that way.

  • ACE35 - Group space 2 is located down the hall (nominally in the westerly direction towards Olden) at the nexus of A-wing (the primary CBE wing), C-wing, and E-wing. There are five desks, a common table, and a large TV with conferencing capabilities. We currently hold group meetings in this space.

  • A214 - The CBE graduate student lounge is on the main A-wing floor. There is tea, coffee/coffee machine, a water dispenser, a microwave, and a sink in this space.

Meetings/Discussion

The group has several regularly scheduled opportunities for research-centric interactions amongst the group and with other groups with similar research interests. These include:

  • ~Weekly Individual Meetings (A325, Wednesdays) - I aim to meet with all junior researcher on a weekly timescale to discuss research progress and future directions. For graduate students (in the front half of the PhD or pursuing a “new project”), we meet weekly. For postdoctoral researchers or later-year graduate students, meetings are every other week. These meetings are typically scheduled on Wednesdays and ensure that time is blocked off for each person. During meetings, students/postdocs are asked to (i) summarize progress and share results as appropriate, (ii) describe any challenges or ask questions, and (iii) outline next steps and targets for next meeting. Depending on project status, it may not be necessary to meet each week to discuss research. This is fine. Please check-in ahead of time so I know that we will not need to meet, and I can use the time for something else. Otherwise, we can also use the time to discuss other aspects of individual development.

  • Weekly Group Meetings (ACE35, Fridays) - We convene weekly as a group to discuss literature, present tutorials, or share research; usually these last about two hours (although I wouldn’t argue with them being shorter!). The first meeting of every month (except January or if falling on a Holiday) is dedicated to literature reviews and tutorials (and food!). The remaining slots are used for research updates. The updates are informal and interactive. These meetings are intended more for the benefit of the researchers than for me as I should have a good handle on what everyone is already doing (but I am happy to be surprised by new things!). In any case, I encourage and prefer interruptions/questions/involvement from everyone. The current schedule can be found here. To balance the load of preparation, the schedule is based on a rotating format wherein different sub-groups are responsible for a given week’s content.

  • Biweekly Joint Group Meetings - Every other week during the academic year, we also convene with the Panagiotopoulos group and the Graves group to share and discuss research with each other. Meetings are over lunch (provided by the PIs) and feature 1-2 junior researchers giving research informal presentations. The current schedule can be found here

  • Biweekly Journal Clubs - Approximately every other week, we meet with members of the Jacobs group for a detailed discussion and analysis of a research article. The article is selected (by myself and Prof. Jacobs) from a set of three articles proposed by the discussion leader. The discussion leader rotates each week, such that each junior researcher leads about once per year.

Slack Channel

A significant portion of daily communication (with me, with other group members, with specific collaborators) takes place using Slack. You should be invited as soon as you join the group. I suggest that you have the app installed/web page opened (if not using the app) during working hours. I prefer this mode of communication as it limits clutter in other areas. I also have a high likelihood of seeing your message and being able to reply easily since the app is on my phone. Certain conversations and discussions are better to have on Zoom or in-person, however.

E-mail

More formal communication may be conducted over e-mail. If you have a need, you can send an e-mail to all current group members using our list-serv e-mail (webbgroup@princeton.edu). Occasionally, members may e-mail other Princeton faculty or external researchers. If this is going to happen, I should be aware of the communication before it takes place. If we are requesting materials/data, the initial communication is probably better established through me first unless I give the go ahead.

Expectations

Me as an advisor

I am committed to supporting you and your development into an independent researcher and critical thinker. You can also expect me to be your strongest advocate and strategist for your long-term aspirations and career goals; if you do not have goals at the start, I will help you develop those and understand your trajectory. I want you to be wildly successful (in my group and beyond); there has never been a successful lab without successful students/junior researchers. I will help you formulate projects and define project directions. I will give you ideas and critiques based on my own experiences and perspectives. I will suggest how to focus your efforts in situations when that becomes necessary. Early on, you will rely a lot on me for knowledge and guidance. Later, although you will continue to make use of my advice, I will increasingly rely on you (to teach me methods, to introduce me to literature, etc.).

Advising style

There are a lot of angles here. An age-old delineation is “hands-off” vs. “hands-on”? That evolves over time (for me, the group, and the individual), but I would argue I am situated somewhere between the two. A guiding principle I inherited from my PhD advisor is that I want students to avoid “spinning their wheels” for too long on something. A little bit of wander and struggle is good/OK, but we want to be consistently moving in the “right” direction. It is critically important that researchers be able to identify and resolve problems on their own, but continually banging your head against the wall and making no progress or, even worse, giving up altogether is not useful. We have a fine balance strike here.

At this stage and current group size, I consider myself as highly accessible. I am almost always willing to discuss things with you outside of regularly scheduled interactions, and it is a common occurence for most members of the group. Typically, if my door is open, it is fine to ask if I have a moment to chat. Otherwise, I routinely exchange messages with people over Slack nearly “around-the-clock,” but I cannot always be counted on to respond, depending on what else I am doing, etc.

Some preferences

My mode of interaction may adjust based on student preferences (as conveyed). That being said, I have my own set of preferences, which may function as a default.

  • I prefer not to micro-manage decisions or approaches towards larger goals. However, I will routinely check you on details so that I understand what you have done and why. This is necessary not only so I can ensure the work is sensible and rigorous (to the level of my understanding) but also so I can properly convey the work externally when appropriate. It will also ensure that you know what you are doing (hint: you should!). Relatedly, if everything with a workflow is going great, then I probably do not care how it is being done. On the other hand, if good progress is not being made or something cannot be done, I will generally be prepared to provide detailed suggestions (even at the coding level).

  • Related to the micro-managing thing, I would prefer not having to follow-up on requests multiple times or providing strict deadlines on tasks. It’s good to head these things off, if I cannot expect something. If there are many requests, it’s probably a good ideato discuss how to prioritize and ensure that we are on the same page. If I ask for something once, and it doesn’t happen/I never bring it up–maybe it was a one-off, and you made a good call to “ignore” it. On the other hand, if I ask multiple times for the same thing, then you should interpret that as being important and I care.

  • I very much prefer collaborative vs. dictatorial interactions. That is, I want myself and the other party (e.g., student, postdoc) to both be involved in defining projects, discussing problems, proposing solutions, etc. The less preferred mode is that I tell you what to do, and then that thing (and maybe only that thing) may or may not be done by the point another dictate is received. It’s not fun, and it’s not what a Ph.D is about. If you have no ideas (hint: you should aim to have some!), I will give you ten. Many times, many of the ideas may not seem good to you or may not work perfectly when followed to the letter. That’s fine; you should understand the problem better than me since you are closer to it. My suggestions should be considered as a reasonable starting point or inspiration. Simply stating something will not work is not very productive. I encourage you to move past that: find what’s good and what’s wrong and use that to progress towards a mutally acceptable solution.

Notes on Demeanor

I am candid in meetings (about what I think, what I do know, what I don’t know, etc.). It’s not that I don’t have a filter; I just don’t see the reason for one (in discussions about reasearch). I encourage you to do the same. I am very hard to actually offend; you probably don’t need to worry about it. If you want to offend me (hint: you shouldn’t), then that can probably be achieved through some display of disrespect. As long as there is mutual respect, you can and should freely speak your mind.

I will often carry strong opinions or positions on things, but I am very reasonable to change my mind if given a good reason. If you disagree with me, that is totally and absoutely fine, but you need to have reasons or “bring receipts. I will expect that during resolution. You should understand that my positions are informed by some fraction of the totality of knowledge/experience on a matter, and this fraction probably exceeds yours early on, if I am being honest. That does not mean I am never wrong, of course, but the scoreboard strongly tilts in my favor. However, one of the most enjoyable things for me is when I can be proven wrong: this is a signal of your growth and an opportunity for me. On that serious note, I would typify most interactions with junior researchers as being pretty lighthearted and playful, even when challenging. I want to do serious science in a fun environment.

I will try to be encouraging and motivating at points, but this is not so natural to me. I default as more of a critical thinker than a cheerleader. You just shouldn’t expect a whole lot of emotional range from me in any direction. Nonetheless, I should always be supportive. I just caution you not to rely overly much on consistent verbal praise as your source of motivation. It’s not a good strategy in my group, and I wouldn’t recommend it more broadly in life.

Funding

When a graduate student joins the group, I am responsible for funding that individual for the duration of their Ph.D (subject to satisfactory progress in the program and in accordance to departmental standards). For postdoctoral researchers, terms of appointment and renewal are described in the offer letter.

Fellowships/External Funding If current/prospective students or postdocs are interested in applying for external funding opportunities, such as fellowships, I highly encourage you let me know, and I will do what I can to help you craft a competitive application. If I think that you are a good candidate for a specific opportunity, I will share that with you as well. Some specific relevant opportunities are listed below:

Graduate Students

Postdotoral Researchers

Undergraduate Researchers

You as an advisee

You will treat me and all other members of the group/collaborators/folks in the Princeton community with respect. You are also expected to uphold the highest level of ethical conduct in research. That is not negotiable.

Throughout your time in the group, I expect that you will be committed to your research and development into an independent researcher. Notice that both are of interest and considered products, for the lack of a better term, of the group. Notice that both are really an investment in you. In fact, the trained individual is much more highly valued (at least to me) than any research product, but externally, the latter is often treated as evidence of the former. Mostly, I want to impress on you that pursuit of a Ph.D or postdoc is a commitment but should be one that directly benefits you, and thus, you should be seriously invested and take ownership of it.

I similarly expect that you will be responsible and accountable for your decisions/actions. It can be hard for people to break out of the “student” mould, especially if continuing straight on highschool –> undergraduate eduction –> graduate education. However, by this time, you really should be a high-functioning adult human being. In fact, I really try to impress this world view even to undergraduates. Are you here to learn? Absolutely, but that is not all. I would consider learning and development to be a necessary byproduct of other obligations during your Ph.D. Life as a graduate student/postdoc in academia can be strange. You’re not exactly a pure student, but it’s also not really like having a regular 9-5. Treating it like the latter is better than the former; however, you have some flexibility in how you conduct yourself and spend your time.

You are expected to ask “dumb” questions. That’s great! I ask plenty. To start, asking questions is not dumb. If we accept the premise that the question is dumb, however, then what does it mean to not ask it? That means that you continue not knowing a thing that you think you really ought to know. The only thing that I want to avoid is using questions as a crutch to avoiding study. So, either ask the question or endeavor to find out on your own. If you don’t ask questions or seek to understand, how do you improve? Corollary: You are expected to make mistakes. Don’t worry about it. This is part of the process. Over time, your goal should be to make fewer overall mistakes and avoid making the same mistake again.

How much am I expected to work? Based on my philosophy/world view, I absolutely do not want to answer this question and provide rigid numbers. This is about your commitment to you and your sweet spot for productivity. If you are developing into an independent researcher, then presumably you are developing skills to manage your time effectively and learning about what works for you. That being said, I can give you some guidance based on my observations/experiences; your mileage may vary. A reasonable baseline number might be averaging ~50 hours/week; this requires pretty consistent effort throughout the week but also affords quality time for other activities. Ideally, this is not a slog for you because you like what you are working on! If it is, then we may want to discuss what we can do about that situation. Some people can work more; some can manage with less. It is important to have some time for rest/leisure/extracurricular activities/hobbies/relationships, and so, generally, it is not advisable to work significantly more than 60 hours/week. You should also be cognizant of burnout and whether you are really being productive during the time that you are investing.

Where and when can I work? You have some flexibility here. You can certainly spend some time working remotely or in off-hours, depending on what is going on. Nonetheless, I believe that groups function best when they are interactive and collaborative, even if not totally in the formal sense (i.e., working together on a specific project). For that reason, there is a lot of value in being around other members of the group, and I strongly encourage you to spend most of your working time in the office during regular operating hours. For one, the office provides a focused environment (or at least it should). Second, this way people (myself and labmates) can regularly find you for impromptu discussions or issues. Brainstorming and bouncing ideas off of labmates is a very useful and productive activity. For me, it was not uncommon to regularly converse with labmates day-to-day about my/their projects and issues; this is hard to do if folks are not co-located. It is also good for the general atmosphere and camraderie of the group. Being away for long extended periods does not usually correlate with increased productivity. Anecdotally, I find people that were previously staunch advocates for remote working discover value in physically being in the office spaces.

What about time away from lab?

Graduate School Official Policy:

“Graduate study is understood to be a full-time commitment on the part of students. Over the course of a year, from the beginning of the fall semester through the following summer, graduate student degree candidates may take up to (but no more than) four weeks of vacation, including any days taken during regular University holidays and scheduled recesses (e.g., the fall- and spring-term breaks and intersession break). The specific periods taken as vacation must not conflict with the student’s academic responsibilities, coursework, research, or teaching, and should be discussed in advance with the student’s director of graduate studies, adviser, or dissertation committee.”*

My addendum:

Vacation/personal days/emergencies. I am not going to rigorously keep track of vacation/personal days, etc. Your schedule is mostly on you, and I trust folks will not abuse this policy. I am generally enthusiastic to hear about your vacation plans, but I would ask for significant advanced notice (>2-3 weeks) if you are going to be gone for a week or more. Ideally, just let me know when you are making plans, and I can adjust plans for me/the group accordingly. Taking a random day here and there is perfectly fine, but you should let me know (a day or two in advance) if this is going to impact any scheduled meetings. If an emergency takes you away, then please try to relay me your status when it becomes reasonably convenient to do so.

Sick days. Absolutely do not come to lab if you are feeling ill. I have no interest in getting sickl neither do others in the group/building. You can work remotely if you feel physically able or take the day off.

Adverse weather. Exceptionally poor weather is rare in Princeton, but it does happen. Remote work is fine if weather is iffy. If this is happening on the day of a major standing meeting (e.g., group meeting), then we will communicate plans for such a meeting over Slack.

The Ph.D Thesis

I consider the journey of more importance than the final product. To me, the receipt of a Ph.D generally connotes that you are capable of independently designing and pursuing original scientific research. The actual thesis document is more or less an illustration that you have done that. Original scientific research expands the scientific body of knowledge in a meaningful way. Note that original implies that the work is new/innovative in some fashion. Do not be surprised then that things can be hard. After all, they should have never been done! We should know something that was not previously known or be able to do something that was not previously possible. Also, when you are awarded a Ph.D, there is a (hopefully correct) perception that you possess some significant technical expertise related to your thesis topic and domain discipline.

How long does it take? As long as it needs. In CBE, the timeline to obtain a Ph.D has a pretty tight distribution and theoretically takes about 5.5 years. Folks shouldn’t erroneously interpret this as just being time served until release though. As our group is relatively new, we have no track record for timeliness, but I expect to and have every motivation to hew closely to this timeline. It’s just a guide, but if you maintain consistent effort, you really shouldn’t have to worry about it. The key is that you have the skills and track record that warrants the degree.

What practically consistutes a Ph.D? I am reticent to offer any specific rules or boxes to check. Provided that you have a proper support system, the Ph.D is really what you are going to make of it. My expectation, however, is that, your original scientific research will be conveyed through multiple (3+) first-author publications and will also be disseminated broadly in other venues (e.g., conference posters/talks). I encourage students to put together manuscripts over the course of the Ph.D rather than submitting a whole host of papers all towards the end; this also seems better for student development. The thesis itself should be straightforward to write if you follow this approach. The document will essentially consist of a grand, cohesive introduction; a presentation of requisite theory/methods; a series of chapters, each likely to reflect the content of a published or submitted manuscript; and a concluding chapter with future directions.

What will be my thesis project? At any given time, we are interested in a combination of projects with funding that must be done and a larger number of not-yet-funded ideas. I aim to find the best match for student’s interests/skills with available projects. I am happy to explore other project opportunities and ideas as long as they identifiably fall within the scope of the group’s expertise and interests. Often, I will aim to have students carry around two distinct but methodologically related projects at around 75%/25% effort. I find that it can be helpful and refreshing to work on something slightly different every once in awhile, but management and progress falters once the number of projects exceeds two.

How do I prepare for my first proposition/general exam? The best way to ensure progression to Ph.D candidacy is to have a productive first year. This involves significant dedicated study to both immersing yourself in specific literature surrounding your thesis topics as well as background/fundamentals of molecular simulation and/or machine learning. It will also the development and demonstration of technical competency.

After we have identified an appropriate thesis topic area for you, our next task will be to identify a short-term, tractable project for you. The conditions for this project are (i) it has a high likelihood of success or appropriate risk mitigation and (ii) it requires skills that are expected to have utility for your larger-scale thesis project. With these conditions, there is a reasonable chance that you can draft and publish a manuscript by the time of your FPO exam. Then, elements of this work can be pivoted into preliminary results for the FPO, thereby providing good evidence required technical prowess to pursue future proposed work. Your committee will likely recognize your demonstrated productivity (I will certainly point it out) and be more inclined to believe that you have the capabilities to produce more thesis-level research.

Students formally join the group in the January following matriculation. In my experience, graduate students remain fairly busy with classes in their second semester, but you have some time to explore literature and initiate your research. It is very useful to generate momentum in the Spring, which sets you up for an awesome, productive summer. (I think back very fondly to my first summer as a graduate student, free of classes and other obligations with the opportunity to really immerse myself in a project.) Coming out of the summer, we ideally want to have a strong foundation of work that can be tidied up for your FPO preliminary results and a potential publication. By mid-October, we should be having dedicated conversations about the contents of your first proposition document. You should aim to have completed draft documents in November, with sufficient time to incorporate a couple rounds of revisions by its submission in the first third of December. More discussion about the first proposition document can be found in the Scientific Communication section.

Undergraduate Research

I am enthusiastic about undergraduates (years 2-4) joining the group to do research via Junior Independent Work (JIW), Senior Theses (ST), or summer programs/internships. There is usually a steep learning curve for computational research. Consequently, I think students benefit most from the research experience if they can commit to more than one semester/summer. Projects are formulated in consultation with me.

Postdoctoral Research

The group is always interested in highly talented/skilled postdoctoral research candidates. Being a postdoc is a very interesting time for intellectual and professional development. It is very important that I understand your interests and goals for a postdoctoral experience and what you want to achieve afterwards. Because of the tight duration of postdoc stints (ca. 1-3 years), we need to be on the same page and develop a strategic timeline that will facilitate success in the group and beyond. If a prospective postdoc is uncertain what they want to do/achieve, I will be more hesitant to bring them into the group because the postdoc is more than a researcher-for-hire to me.

I expect postdocs to conduct research with significant independence and autonomy, guided by high-level instruction. There is also an expectation that they will provide mentorship and leadership for student advisees. Therefore, postdocs are encouraged to involve or avail themselves in their colleague’s academic research pursuits.

Often, postdocs are recruited for specific projects, and they will be expected to make satisfactory progress and commitment to that project. However, that does not mean there are no opportunities to grow a research profile and pursue other interests/skills. I think the two-project mantra is fair for postdocs as well as graduate students, but depending on research progress, it is not unreasonable to dabble in other areas. For any jointly advised postdocs, the pursuit of “side” projects must be agreeable to both myself and the other advisor.