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have experience in computational neuroscience and data mining using machine learning methods. The successful candidate will lead an independent research project dedicated to identifying abnormal neuronal
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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post-doctoral research associate position in machine learning (ML). This position offers a unique opportunity to conduct both basic and applied research in concert with collaborators working on diverse
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pressing challenges. The PIIRS Postdoctoral Fellows Program is integral to that mission. We will award two postdoctoral fellowships to our 2026-27 cohort. PIIRS seeks recent PhDs in the Social Sciences who
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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Research Group "Cluster Algebras" of Dani Kaufman has openings for PhD Student and Postdoctoral Researcher Positions. The group is based at the Max Planck Institute for Mathematics in the Sciences, a
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appointment) in a relevant field, such as geodynamics, seismology, geophysics, or computational science. Ability to sit for extended periods (e.g., 6–8 hours/day). Visual acuity to read computer screens and
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). Below are key aspects of the training program: The Yale CPC Training Program aims to train pre- and post-doctoral fellows in five thematic areas: cancer etiology, cancer outcomes, lifestyle behavioral
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Postdoctoral Research Associate - Improving Sea Ice and Coupled Climate Models with Machine Learning
to develop hybrid models for sea ice that combine coupled climate models and machine learning. Our previous work has demonstrated that neural networks can skillfully predict sea ice data assimilation