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of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large
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focused on Artificial Intelligence (AI)-driven retrosynthesis and reaction prediction. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic
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spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
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! And more: https://www.bowdoin.edu/hr/benefits-perks/index.html Education/Skills Requirements Doctoral Degree required Working knowledge of all aspects of planning and deploying an AI project, including
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transmission of knowledge and understanding. At the same time, Princeton is distinctive among research universities in its commitment to undergraduate teaching.Today, more than 1,100 faculty members instruct
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at the time of accepting the position (a net period of time, which does not include parental leave, military service etc.) good skills in spoken and written English prior experience and knowledge in magnetic
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who meet the following requirements: 1. doctoral degree in the discipline of Earth Sciences, Biology or related, 3. excellent knowledge of computer techniques used in geography and ecology 4. very good
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sleep recordings, pharmacological approaches, and working with rodents in a laboratory setting desired. A strong knowledge of the hippocampus and the brain’s learning and memory circuitry is preferred
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sleep recordings, pharmacological approaches, and working with rodents in a laboratory setting desired. A strong knowledge of the hippocampus and the brain’s learning and memory circuitry is preferred
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets