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Up Directory CCL 22.11.02 Machine Learning Researchers and Engineers -- Computational Biochemistry and Drug Discovery
From: jobs at ccl.net (do not send your application there!!!)
To: jobs at ccl.net
Date: Wed Nov 2 02:57:20 2022
Subject: 22.11.02 Machine Learning Researchers and Engineers -- Computational Biochemistry and Drug Discovery
Machine learning researchers and engineers with impressive records of academic and 
professional achievements sought to join our interdisciplinary team in New York City.  
We will consider candidates at all levels of experience.

This is a unique opportunity to collaborate with our chemists, biologists, and computer 
scientists to expand the groups efforts applying machine learning to drug discovery, 
biomolecular simulation, and biophysics.  Ideal candidates will have demonstrated 
expertise in developing deep learning techniques, as well as strong Python programming 
skills.  Relevant areas of experience might include molecular dynamics, structural biology, 
medicinal chemistry, cheminformatics, and/or quantum chemistry, but specific knowledge of 
any of these areas is less critical than intellectual curiosity, versatility, and a track 
record of achievement and innovation in the field of machine learning.

D. E. Shaw Research (DESRES) develops and uses advanced computational technologies to 
understand the behavior of biologically and pharmaceutically significant molecules at an 
atomic level of detail, and to design precisely targeted, highly selective drugs for the 
treatment of various diseases.  Among our core technologies is a proprietary special-purpose 
supercomputer called ANTON which we designed and constructed to perform molecular dynamics 
simulations more than 100 times faster than the world's fastest general-purpose supercomputers.  
DESRES develops and refines advanced biomolecular modeling methods, software, and machine learning 
techniques on ANTON, as well as on general-purpose supercomputers, in order to pursue both 
internal and collaborative drug discovery programs.  Machine learning techniques are a 
rapidly-growing aspect of our research efforts.  For example, we have developed and published 
neural networks that improve the accuracy of quantum chemistry models, and have trained deep 
learning models to generate optimized molecules for drug discovery.

We take great pride in the caliber of our team, and we offer above-market compensation.  
We also provide generous relocation and immigration assistance to new hires.  In addition, we 
strive to support the personal and professional needs of our team members by offering generous 
benefits, opportunities for community engagement, and a variety of learning and development programs.

To submit an application, please use the link provided below: 

https://apply.deshawresearch.com/careers/Register?pipelineId=597&source=CCL.net

D. E. Shaw Research is an equal opportunity employer, dedicated to the goal of building a diverse workforce. 
We embrace diversity along all dimensions, and respect and value the unique qualities, perspectives, and 
identities of every person in our group. We welcome inquiries from all exceptionally well-qualified applicants, 
regardless of race, color, nationality, national or ethnic origin, religion or religious belief, caste, 
gender identity, pregnancy, caregiver status, age, military service eligibility, veteran status, sexual 
orientation, marital or civil partner status, disability, or status in any other category protected in 
this regard by law in any jurisdiction in which we operate. 

The expected annual base salary for this position is $250,000 - $550,000.  Our compensation package also 
includes variable compensation in the form of sign-on and year-end bonuses, and generous benefits.  
The applicable annual base salary paid to a successful applicant will be determined based on multiple 
factors including the nature and extent of prior experience and educational background.
https://apply.deshawresearch.com/careers/Register?pipelineId=597&source=CCL.net
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Modified: Wed Nov 2 06:57:20 2022 GMT
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