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Postdoc - Deep Learning and Pharmacology @ UCSF

Posted by: UCSF

Posted date: Aug-08-2016

Location: San Francisco, CA

The Keiser lab at UCSF is looking for highly motivated postdoctoral candidates with a background in machine learning, systems pharmacology, computational chemistry, bioinformatics, or related fields. The candidate would work to integrate deep learning with pharmacology. The project involves the design of deep neural networks for the prediction of small molecule binding activities and their role in phenotypic screens.

Qualifications

Desired, but not strictly required, skills include experience with theano, lasagne/keras, TensorFlow, pandas, and sklearn. Expertise with CUDA and/or massive dataset analysis (e.g., NoSQL, AWS, Google Cloud) is a plus. A productive track record with at least profile first-author publication is required. We seek a driven individual who will lead his/her research independently and communicate frequently and clearly to the field.

Environment

Just north of Silicon Valley, the lab's location at UCSF Mission Bay directly adjoins SoMa district and heart of SF’s 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(at)keiserlab.org. Please reference “postdoc-dnn”.

Job Title Postdoc - Deep Learning and Pharmacology (at) UCSF
Post Details
Email apply(at)keiserlab.org
Employer's Website www.keiserlab.org
Category
Job Discipline Job Discipline -> Computational Biology
Job Classification Job Classification -> Postdoctoral Researcher
Job Type Job Type -> Full-time
Location San Francisco, CA
Key Words machine learning, theano, systems pharmacology
Start Date 2016/09/01
Deadline