409 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship positions
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machine learning with single-cell genomics, spatial omics, and systems biology, supported by strong collaborations across UBC and internationally. Project Recent advances in single-cell and spatial omics
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per year. The successful candidate will be able to teach Introduction to Comparative Politics, in addition to an intermediate-level European politics course and a thematic course in a more specific area
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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the possibility of extension. For more details on our research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu For questions, please email mweber
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are template based and all US measurements are auto-populated into templates for increased accuracy and efficiency. Fourteen fellowship-trained, subspecialized expert faculty perform both image interpretation
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required. § The prospective applicant does not have to be an expert in localization. However, good knowledge of wireless communications, digital signal processing, and computer algorithms is required
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the opportunity to work at the intersection of AI and health sciences, focusing on developing machine learning approaches to diagnosing musculoskeletal pain conditions, including low back pain and osteoarthritis
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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interest in, the political and societal implications of AI and machine learning. Proficiency in English sufficient to discuss research with colleagues and report findings clearly in writing. Motivation