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Field
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machine learning. The specific goal is to extend new and existing visualization environments to support efficient and precise annotation of histopathology images using a combination of expert human review
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website: https://profiles.mountsinai.org/louai-labanieh This position is covered by a collective bargaining agreement between the ISMMS and the Sinai Postdoctoral Organizing Committee - UAW. Wages and
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, and formulation of clinical study design, image processing, machine learning, and statistical analyses to illuminate specific research questions. Among the machine learning techniques, deep learning
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Details Title Postdoctoral Fellow in Geometric Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Applied Math Position Description A
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modeling, machine learning methods, and applications involving text and other non-traditional data sources. The fellow will contribute to and extend research in these areas, engaging in projects that develop
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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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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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quantitative methods at the interface of statistical learning, experimental design, and optimization to address challenges created by the operationalization of AI within partner organizations. The Postdoctoral
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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. This program
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neuroscience. The position is open under specific projects as well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand