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Position: Machine Learning Scientist
Institution: Profluent
Location: Berkeley, California, United States
Duties: Design and develop state-of-the-art deep learning methods for protein sequence, structure, and function prediction and apply them to protein design; Collaborate with Biology team to design and characterize novel designed biomolecules; Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings; Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company
Requirements: PhD in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field; Experience with conceiving of, implementing, and developing novel machine learning techniques; Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS); Experience with modern deep learning frameworks such as Pytorch or Jax
   
Text: Machine Learning Scientist Design and develop state-of-the-art deep learning methods for protein sequence, structure, and function prediction and apply them to protein design; Collaborate with Biology team to design and characterize novel designed biomolecules; Implement, analyze, and interpret multiple computational approaches and present results to colleagues in regular update meetings; Work within a collaborative, fast-paced, interdisciplinary team across biology and machine learning to help shape the scientific and strategic vision of the company PhD in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field; Experience with conceiving of, implementing, and developing novel machine learning techniques; Publications at major machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, Nature Biotech, Nature Methods, PNAS); Experience with modern deep learning frameworks such as Pytorch or Jax
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