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to the development of remote sensing algorithms, simulation and modeling capabilities, and artificial intelligence/machine learning (AI/ML) methods in support of the goals of the joint NASA/USGS Landsat mission
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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SPECIFICS Postdoctoral Scholar (Machine Learning or Artificial Intelligence in Molecular and Cellular Biology) The National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS
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. Candidates will collaborate closely with interdisciplinary research groups advancing materials discovery through the convergence of computational chemistry, machine learning, and agentic science. This full
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as a member of the GHER contributing to the EU research project COMEDI in a consortium of 11 leading partners in the field of data assimilation and deep learning. A successful applicant will develop
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geoscientific process models, as demonstrated by presentations, publications and/or repositories Expertise in applying Bayesian statistical methods, machine learning methods, or related statistical inference
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computing, obtained within a maximum of 7 years; application of machine learning and deep learning methods to remote sensing images; proficiency in programming (R, Python, or similar); ability to work