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<font size="4"><b>Postdoctoral researcher position in deep learning at NYU<br></b></font><br>We
are looking for a postdoctoral researcher to join our efforts in
developing deep learning methods for computer vision, especially
medical image analysis. The candidates are expected to have strong
machine learning skills to work on methodological advances - improving
accuracy, robustness, and explainability of deep neural networks.<br><br><div>We are particularly interested in candidates who wish to work on some of the following topics:</div><div>- reinforcement learning,</div>- vision transformers,<br>- Bayesian neural networks,<br><div>- causal inference,</div><div>- transfer learning,</div>- self-supervised learning.<br><br>The candidate will be based primarily at the NYU School of Medicine
and will also work in close collaboration with researchers at NYU
Center for Data Science, NYU Courant, and NYU Abu Dhabi. Regular
collaborators of our group include <a href="https://kyunghyuncho.me/" target="_blank">Kyunghyun Cho</a>, <a href="https://math.nyu.edu/~cfgranda/" target="_blank">Carlos Fernandez-Granda</a>, <a href="https://nyuad.nyu.edu/en/academics/divisions/engineering/faculty/farah-emad-shamout.html" target="_blank">Farah Shamout</a>, and <a href="http://www.spchopra.org/" target="_blank">Sumit Chopra</a>.<br><br>Expected qualifications:<br>- PhD (or near completion) in machine learning or related discipline,<br>- experience with training deep neural networks for computer vision tasks,<br>- excellent programming skills,<br><div>- ability to work in an interdisciplinary team with members at various levels.</div><br>Some examples of our recent work:<br>- <a href="https://arxiv.org/pdf/2002.09572.pdf" target="_blank">The break-even point on optimization trajectories of deep neural networks</a>,<br>- <a href="https://www.sciencedirect.com/science/article/pii/S1361841520302723" target="_blank">An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization</a>,<div>- <a href="https://arxiv.org/pdf/2011.14036.pdf" target="_blank">Differences between human and machine perception in medical diagnosis</a>, <br></div><div>- <a href="https://arxiv.org/pdf/2012.14193.pdf" target="_blank">Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization</a>,</div><div>- <a href="https://arxiv.org/pdf/2010.09750.pdf" target="_blank">Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability</a>.</div><br>For full consideration, please apply no later than the 30th of June 2021.<br>Start date: as soon as possible.<br><br>The initial appointment will be for a year, with the option to renew further, depending on performance.<br><br>To be considered for this position, please send your CV with a list
of publications and a brief motivation letter (3-5 sentences is enough)
to <a href="mailto:k.j.geras@nyu.edu" target="_blank">k.j.geras@nyu.edu</a>. Please use the string “[deep learning postdoc 2021]” as the subject of the email.<br><br>Best,<br>Krzysztof J. Geras<br><br>NYU
is an Equal Opportunity Employer and is committed to a policy of equal
treatment and opportunity in every aspect of its recruitment and hiring
process without regard to age, alienage, caregiver status, childbirth,
citizenship status, color, creed, disability, domestic violence victim
status, ethnicity, familial status, gender and/or gender identity or
expression, marital status, military status, national origin, parental
status, partnership status, predisposing genetic characteristics,
pregnancy, race, religion, sex, sexual orientation, unemployment status,
veteran status, or any other legally protected basis. Women, racial and
ethnic minorities, persons of minority sexual orientation or gender
identity, individuals with disabilities, and veterans are encouraged to
apply for vacant positions at all levels.
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