415 machine-learning-"https:" "https:" "https:" Postdoctoral positions in United States
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2026 Group or Departmental Website: https://mellab.stanford.edu/(link is external) https://spoglab.stanford.edu/(link is external) How to Submit Application Materials: To apply, please submit
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-changing careers. Learn more about Sandia at: https://www.sandia.gov *These benefits vary by job classification. What Your Job Will Be Like: We are seeking motivated postdoctoral candidates to advance
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an anticipated start date of August 1, 2026. This particular position is mainly supported by the Air Force Office of Scientific Research (AFOSR) grant on Hybrid Control, Computation and Machine Learning, and will
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, inferential and spatial analysis, as well as integrating machine learning techniques, and leading and drafting manuscripts. We will support and encourage the candidate’s independent research interests
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machine learning and computational methods Work with medicinal chemists for drug discovery projects Act as key member of a multidisciplinary drug discovery project team, assisting with development
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computing and/or cloud computing; familiarity with Earth system models through model development, model execution, and/or model performance diagnoses; applied mathematics methods such as machine learning
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options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits
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at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited to): Perform quality checks of brain PET/MRI cognitive, clinical, genetic
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Qualifications: PhD in a relevant field is required; relevant fields include but are not limited to epidemiology, statistics, biostatistics, machine learning, data science, or other quantitative fields. Required
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA