Junior Principal Investigator Sessions – WK01

Sandrine DudoitDivision of Biostatistics and Department of Statistics

University of California, Berkeleywww.stat.berkeley.edu/~sandrine

ISMB 2016 – Intelligent Systems for Molecular BiologyOrlando, FL

July 10, 2016

Version: 10/07/2016, 06:34

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Agenda

How to outline an individualized career development plan tobecome a successful PI.

• This session will cover the concept of having an active role onyour own career development and empowering trainees tohave a strategy when picking mentors and pursuing training.

• This encompasses making very conscious decisions aboutwhat your niche or “brand” will be when looking for jobs(academic or not).

• Having an “IDP” is a requirement for all NIH grants on the“training” phases and it is also being requested by privatefoundations.

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Caveat Emptor

• Giving advice.“Le plus excellent et divin conseil est d’apprendre a s’etudieret a se connaıtre soi-meme.”“The most excellent and divine of advice is to learn to studyand know yourself.”(Pierre Charron, Le traite de la sagesse, 1601)

• Everyone is different/One size does not fit all.

• Things rarely (never!) go according to plans.

• I’ve never had a career plan.I My studies and career have been guided by encounters, with

persons and research questions.I My research is oriented by problems that I am excited about

and believe are important and interesting.I I have been lucky in that these problems have also been timely

and of great interest to the community.

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Caveat Emptor

I But I also work hard. And although I didn’t have a career plan,I tackle these problems in a principled, rigorous, and honestmanner.

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Outline

1 My Journey

2 What Is an IDP?

3 A Career in Interdisciplinary Research

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My Journey

• I am a Professor in the Division of Biostatistics andDepartment of Statistics at UC Berkeley.

• My research and teaching activities concern the developmentand application of statistical methods and software for theanalysis of biomedical and genomic data.

• Statistical methodology. My methodological research interestsregard high-dimensional inference and include exploratory dataanalysis (EDA), visualization, loss-based estimation withcross-validation (e.g., density estimation, regression, modelselection), and multiple hypothesis testing.

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My Journey

• Applications to biomedical and genomic research. Much of mymethodological work is motivated by statistical inferencequestions arising in biological research and, in particular, thedesign and analysis of high-throughput microarray andsequencing gene expression experiments, e.g., RNA-Seq fortranscriptome analysis and genome annotation and ChIP-Seqfor DNA-protein interaction profiling (e.g., transcription factorbinding). My contributions include: exploratory data analysis,normalization and expression quantitation, differentialexpression analysis, class discovery, prediction, integration ofbiological annotation metadata (e.g., Gene Ontology (GO)annotation).

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My Journey

• Statistical computing. I am also interested in statisticalcomputing and, in particular, reproducible research. I am afounding core developer of the Bioconductor Project(www.bioconductor.org), an open-source andopen-development software project for the analysis ofbiomedical and genomic data.

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My Journey

• 1988–1992: BSc in Mathematics, Carleton University, Ottawa,Canada.

• 1992–1994: MSc in Probability Theory, Carleton University,Ottawa, Canada. Advisor: Don Dawson.

• 1994–1999: PhD in Statistics, University of California,Berkeley. Advisor: Terry Speed.

• 1999–2001: Postdoc in Biochemistry, Stanford University.Advisor: Pat Brown.

• 2001–: Professor of Biostatistics and Statistics, University ofCalifornia, Berkeley.

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My Journey

Aspects of my doctoral and postdoctoral education that I havefound particularly useful.

• Statistical consulting course. Department of Statistics, UCBerkeley.

• Internship in wet-lab. Walter and Eliza Hall Institute (WEHI),Melbourne, Australia.

• Doctoral fellowship for interdisciplinary research. Program inMathematics and Molecular Biology (PMMB).

• Postdoctoral fellowship in wet-lab. Brown Lab, Department ofBiochemistry, Stanford University.

• Practice with grant proposal writing. Assist PI with RO1proposals, apply for own fellowships.

• Participation in small, focused conferences, workshops, andshort-courses. Latest research developments, open questions,networking.

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My Journey

• Bioconductor Project. Software development, reproducibleresearch.

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What Is an IDP?

What is an Individual Development Plan (IDP)?Quoted from NIH Training Center (NIHTC).

• “An Individual Training & Development Plan (IDP) is a toolto help support, plan, and track your career development andlearning opportunities.”

• “With IDP services from NIHTC, you can learn how to buildan IDP based on your greatest strengths, address areas forgrowth, and confidently discuss your IDP with yoursupervisor.”

• “An experienced consultant, versed in mentoring and coachingManagement Interns and Presidential Management Fellows,will work with you from a holistic perspective. Taking accountof all considerations, you can develop a plan to serve as aunique contributor aligned with the NIH mission.”

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What Is an IDP?

• “The relationship with the IDP consultant is confidential andimpartial.”

• “NIHTC can also bring IDP best practices on-site to yourteam or office.”

• Two 50-minute sessions: $299.

https://trainingcenter.nih.gov/idp consulting.html13 / 25

What Is an IDP?

What are the benefits of IDP Consulting?Quoted from NIH Training Center (NIHTC).

• Develop an Individual Development Plan customized to yourneeds.

• Identify, clarify, and commit to goals based on your prioritiesand professional goals.

• Create and develop strategies for goal achievement.

• Track progress toward your goals.

• Understand, evaluate, and strengthen your technical andnon-technical competencies.

• Practice confidently discussing strategies for aligningexpectations with those of your supervisor.

• Make the most out of a recent promotion, job opportunity, orother developmental prospect.

• Analyze alternatives and solutions.14 / 25

Interdisciplinary Research

Beware of jack-of-all-trades-master-of-none one.

• What is a bioinformatician/computational biologist/datascientist? Is it a biologist that is computer savvy or astatistician that has dabbled with genomic data?

• Don’t try to do everything yourself.

• The best approach to interdisciplinary research is not just oneperson that knows a little bit about everything, but rather ateam of experts in component disciplines, i.e., biologicalsubject-matter, statistics, computer science.

• This doesn’t mean statisticians should be ignorant of biologyand vice versa.

• On the contrary, we each need to learn a minimum aboutother fields in order to have a common language,communicate well, and be aware of the various aspects,challenges, and pitfalls of an interdisciplinary research project.

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Niche/Brand

• Clearly define your area of expertise.

• Look for projects that you are excited about, that you have theexpertise to tackle, for which you have the potential to makea contribution, for which you have the right environment, andthat are relevant and of interest to the community.

• Be specific about project goals, have well-defined andself-contained scientific questions.One of the hardest steps can be the translation of a biologicalquestion into a statistical question, i.e., the specification of aparameter of interest.

• Start from subject-matter question vs. hammer looking fornail.

• Get involved early, at experimental design stages, know howdata are generated.

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Niche/Brand

• Decide on point of entry. Tackle pre-processing (e.g.,normalization) or focus on higher-level analyses (e.g., classdiscovery).Cf. Feasibility.

• Don’t reinvent the wheel. Survey the literature in differentfields, consult with experts in other fields.

• Don’t loose the forest for the trees.

• Avoid jargon, hype, fluff.

• Communicate throughout the project. Joint group meetings,interactions at faculty, postdoc, and graduate student levels.

• Practice makes perfect. Start early, do not get discouraged bysetbacks, focus on long/middle-term goal, learn from thejourney.

• Be excited about your work, makes a world of difference whenputting in long hours.

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Training

As graduate student, postdoc, or even junior faculty.

• Dry-lab and wet-lab co-mentors. Choose based on research,but also mentoring skills and personal relationship.

• Interact with peers.

• One project, two dissertations.

• Courses. Enroll or sit in courses, e.g., biology and computingfor a statistician.

• Workshops. External, e.g., Bioconductor, or internal, e.g.,Computational Genomics Resource Laboratory, UC Berkeley(qb3.berkeley.edu/cgrl).

• Lab meetings, journal clubs.

• Publishing. Get involved in writing of articles.

• Grantsmanship. Practice with grant proposal writing, byassisting PI with proposals and applying for own fellowships.

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Communication

• Communicate. Communicate regularly with the persons thatwill evaluate your dissertation/case, make sure they knowwhat you are working on and are aware of your progress, sothat, if needed, you can revise your plan.

• Team of mentors. On the scientific front, dry-lab and wet-labco-mentors.On the admin front, mentors that can help with navigatinguniversity and funding agency bureaucracy, advise with jobapplication, tenure case, career decisions.

• Team of collaborators. Choose not only based on on-paperacademic record, but on ability to communicate and get alongwith them.I value more and more the personal aspects of a collaboration,the ability to enjoy working with collaborators.

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Communication

• Publishing. Judicious choice of message and journal for eachpublication; one project, two publications; don’t let “the bestbe the enemy of the good”.

• Internal exposure. Give or attend seminars and short courseswithin your own institution.

• External exposure. Editorial work, conferences, short courses.Nowadays, blogs, Twitter?

• Curriculum vitae. Write a compelling CV based on yourexpertise and accomplishments.

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The Plan

• Niche/Brand. Identify area of expertise and, within that area,well-defined and self-contained scientific questions.

• Identify your strengths and weaknesses.

• Devise training program of courses, workshops, reading list,co-mentors, and team of collaborators.

• Apply for suitable fellowships and grants, after surveyinggovernment and private funding agencies and discussions withmentors.Cf. Lucia Peixoto’s presentation.

• Work hard ... and enjoy the journey!

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Les Devises Shadok

Figure 1: Les devises Shadok. “En essayant continuellement on finit parreussir. Donc: Plus ca rate, plus on a de chances que ca marche.” “Ifyou keep trying you’ll eventually succeed. Therefore: The more you fail,the more chances you have to succeed.”

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Les Devises Shadok

Figure 2: Les devises Shadok. “Si ca fait mal c’est que ca fait du bien!!”“If it hurts it means it’s good for you!!”

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Les Devises Shadok

Figure 3: Les devises Shadok. “Pourquoi faire simple quand on peut fairecomplique?!” “Why makes things simple when they can becomplicated?!”

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Les Devises Shadok

Figure 4: Les devises Shadok. “Quand on ne sait pas ou l’on va, il faut yaller!! ... ... et le plus vite possible.” “When you don’t know whereyou’re going, you better go ... ... and the fastest possible.”

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