A CAREER in Computational and Data-Driven Chemistry

1. A CAREER in Computational and Data-Driven Chemistry • Johannes HachmannDepartment of Chemical and Biological Engineering • Graduate Program in Computational and Data-Enabled Science and Engineering • New York State Center of Excellence in Materials InformaticsUniversity at Buffalo, The State University of New York • NSF CISE CAREER Workshop, Alexandria (VA) • (8 April 2019)

2. About myself • grew up near Münster (North-West Germany, close to Netherlands) • 1999–2003: University of Jena (Germany): undergraduate in Chemistry • 2003–2004: University of Cambridge (UK): DiplChem (≈MSc) in Chemistry • 2004–2009: Cornell University: MSc & PhD in Chemistry • 2009–2014: Harvard University: Postdoc, Research Associate in Chemistry • since 2014: University at Buffalo: Assistant Professor in Chemical Engineering

3. About myself • grew up near Münster (North-West Germany, close to Netherlands) • 1999–2003: University of Jena (Germany): undergraduate in Chemistry • 2003–2004: University of Cambridge (UK): DiplChem (≈MSc) in Chemistry • 2004–2009: Cornell University: MSc & PhD in Chemistry • 2009–2014: Harvard University: Postdoc, Research Associate in Chemistry • since 2014: University at Buffalo: Assistant Professor in Chemical Engineering • Applications: Chemical Physics, Chemistry, Materials • Tools: Computational and Data Science, Informatics

4. The White House Materials Genome Initiative

5. The White House Materials Genome Initiative

6. CAREER proposal

7. CAREER proposal: Scope • “Award is for 5 years. One needs to find the right scope – too ambitious vs. not ambitious enough, how did you pick the problem?” • tools and techniques for long-term research program • “instrument” (tools + techniques) with lasting utility • build foundations for next 10-20 years • well-defined goals but in principle open ended • need for a science driver application

8. CAREER proposal: Research and Education • “Integration of research and education is a critical aspect of the proposal. How did you plan your education component as well as your plan to integrate this with your research component?” • educational needs for my own group due to emerging character of field(i.e., data science in chemistry/chemical engineering) • involvement in CDSE graduate program, several initiatives I had already launched • education sections fleshed out before research sections • many schools have existing programs to piggy-back on • large, integrated component of proposal, not just add-on! • reviewers recognize the difference

9. CAREER proposal: Mentor • “Did you have a mentor, how much did s/he help?” • yes, but limited utility for CAREER proposal (too far removed) • asked tenure-track friends for advice, criticism • “panel before the panel”

10. CAREER proposal: Deadlines • “The deadline is in July, when did you start?” • 1st time around too late (mid-May, interrupted by conference season) • starting early is easier said than done – everything has deadlines… • 2ndtime right after rejection • fixed all criticism right away, used remainder of time to polish • work on project with startup funding • produce preliminary results for credibility

11. CAREER proposal: Examples • “Did you have some example projects if so how did you get them?” • yes, from friends and colleagues (alas not in the same area) • referee reports would have been more useful

12. CAREER proposal: The right directorate • “Did you talk to one or more NSF PDs, how did you pick the PD, how difficult was it finding the right match, did you switch the directorate/division/PD after the first or second declines?” • 1st try: CHE, PD moved to ACI • 2nd try: ACI (secondary: CHE, CBET, DMR, CDS&E) • thought cross-disciplinary character would be asset • instead opened me up to (off-topic) criticism • 3rd try: ACI (secondary CHE) • careful communication with PDs beforehand

13. CAREER proposal: Reviews and feedback • “If your earlier attempts did not work, did the reviews help, how much weight did you give to these reviews, did you change problem or topic or area?” • mixed messages, some of criticism was frustrating • secondary divisions did not necessarily help • there was clearly the need to make my case better • disappointing 2nd attempt: fixed relatively minor criticism from 1st attempt, but evaluation became a good bit worse • typically not the same reviewers • stuck to my guns, no change in problem/topic/area, but I reframed the issue • made more compelling case for what I thought is important work

14. CAREER proposal: Proposal writing • “Talk about your proposal writing/preparation guidance with examples.” • approach proposal like legal argument • task: make compelling case for project • map out structure, logic, lines of arguments first, fill in details later • accessible language, engaging read • highlight key points to aid panel discussion • use program solicitation as guideline; make sure that it hits all the spots • get LOCs to demonstrate that you are connected, have support • pick your battles • you cannot hit every opportunity, but CAREER is an important one • better do fewer, high-quality proposals rather than many low-quality ones

15. CAREER proposal: Additional advice • “What additional advice, from your personal experience, would you give to PIs as they plan and write their CAREER proposals?” • make your mark, claim your stake! • write about what you want to be know for (e.g., when you go up for tenure) • think big picture (which is actually a lot of fun)! • CAREER is not your regular project proposal • don’t forget about concrete issues you will tackle • take part in panels to better understand decision making process • e.g., people take data management seriously • talk to your PD – it’s intimidating but can be really helpful • take education and integration with research seriously! • this is not just an afterthought!

17. Questions?