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start date. Preferred Qualifications: Research experience in computer vision, NLP, geospatial data systems, or high-performance computing. Brief Description of Duties: The Postdoctoral Associate will
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analysis, machine learning, mathematics of data scienceMathematical modeling and manifold learning of high-dimensional data geometry, with theoretical foundations and applications in evolutionary biology and
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brain MRI analysis, statistical analyses, as well as data acquisition and machine learning. Experience with stroke and federated learning is a plus. Job ID REQ20177725Posted Date 08/05/2026 Current
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at the realization of large-scale diffusion language models and flow models. Specifically, tasks include but are not limited to: training using parallel GPUs, improving diffusion language models and flow models
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analyse electrochemical free-energy landscapes and connect elementary-step energetics to catalytic performance apply machine-learning interatomic potentials and microkinetic models where appropriate
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and machine learning with density functional theory, or other similarly relevant computational methods, to advance understanding of materials design predictions for 2D and 3D systems with electronic and
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and growing community. Learn more here: https://research.duke.edu/prospective-postdocs/. Screening of Applications Screening continues until position is filled. Job Code: 00003820 POSTDOCTORAL ASSOCIATE
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of machine learning and advanced molecular dynamics techniques for molecular simulations and to study Nucleic acids structures and their interactions. For more information, please visit https://nyuad.nyu.edu
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working on the LHCb experiment at the Large Hadron Collider. The successful candidate will focus on developing LHCb’s real-time data analysis systems, including the GPU-based software trigger. This work
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to think independently, in human-AI interaction. You will connect the project's technical work with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction