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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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Assistant Director, Baylor Synthesis & Drug-Lead Discovery Laboratory & Associate Research Professor
compound identification and optimization with collaborating PIs Oversee structure-activity relationship studies and organic chemistry campaigns Guide transitional studies of promising compounds Maintain
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National Institutes of Natural Sciences, National Institute for Physiological Sciences | Japan | 24 days ago
job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description [Background
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Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No Offer Description This project aims to explore and develop novel concepts and
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motivated postdoctoral researcher that is interested to work on quantum information and mathematical optimization in the group of Felix Huber (https://huberfe.github.io/ ). Topics they can expect to work
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is required, particularly in the development of digital solutions, data processing and integration, computational modelling, or optimization algorithms. Preference will be given to candidates with
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quantification of ocean carbon storage efficiency, enabling more reliable MRV and better planning and optimization of large-scale carbon removal interventions. Key Responsibilities The postdoctoral researcher will
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: Requires a doctoral degree in relevant fields (e.g. neuroscience, biology, psychology, computer science). A pending
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writing content for grant applications. Will collaborate with the team to design, optimize, and standardize experimental and analysis pipelines to accelerate high-quality publications. Will review trainee
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theoretical foundations of artificial intelligence, including statistical/machine learning theory, optimization, and deep learning. Successful candidates must have a strong record of research and teaching and