|CCL 19.02.05 Postdoc - Deep Learning and Molecular Dynamics - UCSF, San Francisco, CA|
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To: jobs at ccl.net
Date: Tue Feb 5 18:37:39 2019
Subject: 19.02.05 Postdoc - Deep Learning and Molecular Dynamics - UCSF, San Francisco, CA
The Keiser lab at UCSF (https://www.keiserlab.org) is looking for highly motivated postdoctoral candidates with a background in machine learning, molecular dynamics, computational chemistry, or related fields. The candidate would work to integrate deep learning methods with molecular dynamics (MD) simulations. The project involves the design and testing of efficient computational ligand-protein interaction representations for the analysis of MD trajectories using convolutional neural networks. # Qualifications Python expertise required. PyTorch or Chainer experience preferred. Desired, but not strictly required, skills include experience with pandas and sklearn. Expertise with massive and/or distributed dataset analysis is a plus. MD trajectories will be provided by expert partners and the project will proceed under an established collaboration. A productive track record with at least one first-author publication is required. We seek a driven individual who will hit the ground running, lead her/his research independently, and communicate frequently and clearly to the field and industry partners. # Environment Just north of Silicon Valley, the labs location at UCSF Mission Bay directly adjoins SoMa district and the heart of SFs tech and artificial intelligence startup scene. # How to apply Interested candidates should submit a CV and arrange that three letters of reference be sent directly to apply^-^keiserlab.org. Please reference "postdoc-dnn-md". UCSF is an equal opportunity employer.NOTE THAT E-MAIL ADDRESSES HAVE BEEN MODIFIED!!!
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