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therapies for cancer, as well as metabolic, neurodegenerative, autoimmune, and infectious diseases. Job description Postdoctoral projects will combine catalyst engineering, computational simulation
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‑on experience with common machine learning / deep learning frameworks (eg. PyTorch or JAX) applied to biological or structural data. Solid Python programming skills, with experience building maintainable and
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data issues. Utilizing machine learning techniques as appropriate for data analysis. Developing computing programs and software to support research initiatives. Applying new methodologies to real-world
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capabilities to aid in the predictive engineering of biological systems, such as proteins, as part of the NIST Engineering Biology Program. Develop artificial intelligence and machine learning analysis pipelines
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
should have a strong background in data science, machine learning, remote sensing, wildfire science, or a related field. Experience with deep learning frameworks, satellite observations (e.g., Sentinel
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
and related activities. Strong programming skills are a must, including experience with machine learning. Good written and oral communication skills in English are important. Point of Contact Mikeala
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. Additional background in renewable energy, surface science, catalysis, and/or machine learning. Strong programming skills in Python and some exposure to machine learning. Ph.D. in Materials Science, Physics
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 24-Feb-26 Location: Brooklyn, NY Categories: Academic/Faculty Internal Number: 182085 POSTDOCTORAL ASSOCIATE New York
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Date: August 15, 2026 (negotiable) Specialty Areas: Computational Linguistics, Language Acquisition, Cognitive Modeling, Machine Learning The Department of Linguistics at the University of Michigan
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machine learning with single-cell genomics, spatial omics, and systems biology, supported by strong collaborations across UBC and internationally. Project Recent advances in single-cell and spatial omics