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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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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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individuals and patients. These projects involve large-scale neuroimaging data collection at 3T and 7T, computational modeling of brain responses using machine learning methods, and cross-institutional clinical
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and
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demonstrated track record in protein structure modelling methods, with hands‑on experience in protein or biologics design and engineering. Hands‑on experience with common machine learning / deep learning
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mutual agreement. Appointment Start Date: As soon as possible Group or Departmental Website: https://med.stanford.edu/solutions.html (link is external) How to Submit Application Materials: Please submit
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About the Opportunity Job Summary The Data-Driven Renewables Research (D2R2) group led by Dr. Peter Schindler is accepting applications for a postdoctoral research associate in the field
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partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course
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in image processing and analysis, including deep learning (e.g., CNNs) experience with correlative imaging workflows and 2D/3D registration techniques strong programming skills in Python and/or C/C
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Episteme, Condensed Matter Theory Group Position ID: Episteme-Condensed Matter Theory Group-POSTDOC [#31188] Position Title: Position Type: Postdoctoral Position Location: Cambridge, Massachusetts