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Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability
Harvard University
Details
Posted: 28-Mar-23
Location: Cambridge, Massachusetts
Salary: Open
Categories:
Academic/Faculty
Engineering
Internal Number: 12302
School: Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area: Computer Science
Position Description:
I'm always looking for longer terms postdocs (e.g. 2 years) that will be a good fit for research directions in the lab. You can get a sense of what we do by looking at my webpage finale.seas.harvard.edu and our group's webpage https://dtak.github.io/ — we work on probabilistic models, reinforcement learning, and interpretability + human factors. Our websites are also a good place to learn more about us.
About Us
Finale Doshi-Velez is a Gordon McKay Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. She completed her MSc from the University of Cambridge as a Marshall Scholar, her PhD from MIT, and her postdoc at Harvard Medical School. Her interests lie at the intersection of machine learning, healthcare, and interpretability. For more information, please visit: https://finale.seas.harvard.edu
About Us
Finale Doshi-Velez is a Gordon McKay Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. She completed her MSc from the University of Cambridge as a Marshall Scholar, her PhD from MIT, and her postdoc at Harvard Medical School. Her interests lie at the intersection of machine learning, healthcare, and interpretability. For more information, please visit: https://finale.seas.harvard.edu
Basic Qualifications:
I expect Postdocs to have completed their PhD in machine learning, math, stats, physics, or some other technical area.
Additional Qualifications:
Postdocs should also already have significant experience in some area of statistical inference/optimization; you will have the chance to mentor both undergraduate and graduate students in these areas (as it relates to joint projects).
A commitment to support diversity, equity, and inclusion/belonging in an academic setting is a must.
A commitment to support diversity, equity, and inclusion/belonging in an academic setting is a must.
Contact Information:
https://dtak.github.io/joining/
Contact Email: finale@seas.harvard.edu
Special Instructions:
Please contact me through the joining section on my website to learn about what specific openings I have. The interview process consists of you giving a talk to the lab and then I will follow up regarding additional 1-1 interviews with me, group chats with students in the lab, etc. All qualified applicants will receive consideration.
Equal Opportunity Employer:
Harvard is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.
About Harvard University
Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment of over 20,000 degree candidates, including undergraduate, graduate, and professional students. Harvard has more than 360,000 alumni around the world. The University has twelve degree-granting Schools in addition to the Radcliffe Institute for Advanced Study, offering a truly global education. Established in 1636, Harvard is the oldest institution of higher education in the United States.
More Jobs from This Employer
https://main.hercjobs.org/jobs/18379204/postdoctoral-fellowship-in-reinforcement-learning-probabilistic-methods-and-or-interpretability
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