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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is
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complex software systems for large-scale research projects, with a focus on education technology and generative AI-based tools. Leverage recent breakthroughs in machine learning and natural
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organization skills Interest in learning and strengthening existing skillsets Strong technical and programming skills, familiarity with current deep learning techniques, with a focus on computer vision Special
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-production digital imaging in a Mac-based computer environment. Develop and maintain organized file structures, asset libraries, and archiving systems to ensure efficient retrieval, backup and long-term
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an exciting clinical trial exploring muscle-controlled robotic systems, pushing the boundaries of human-machine interfacing and neuroprosthetics. You will work at the intersection of neuroscience, engineering
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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environments for statistical analysis (e.g., MATLAB, R, or Stata); · Creating and managing very large datasets; · Machine learning skills. Basic Qualifications A Ph.D. in any business discipline
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research on Riemannian Optimization. The ideal candidate has a
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with an interdisciplinary team of statisticians, physicians, computer scientists, and health policy researchers. The successful candidate will lead development of variable importance measures – including