Machine learning engineers with impressive records of academic and professional achievements sought to join our interdisciplinary team in New York City.
This is a unique opportunity to collaborate with our chemists, biologists, and computer scientists to expand the group's 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 is an independent research group focusing primarily on molecular simulations of proteins and other biological macromolecules with the long-term goal of transforming the process of drug discovery. We have developed multiple generations of a special-purpose supercomputer, ANTON®, capable of executing molecular dynamics simulations orders of magnitude faster than was previously possible, as well as software tools aimed at achieving major scientific advances in the fields of biochemistry and molecular biology. 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. This full-time role also offers full benefits, generous relocation assistance, and a collegial working environment.
To submit an application, please use the link provided below:
D. E. Shaw Research is an equal opportunity employer, dedicated to the goal of building a diverse workforce. We welcome inquiries from all exceptionally well-qualified applicants, regardless of race, color, nationality, national or ethnic origin, religion or religious belief, caste, gender, 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.
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