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University of California, Berkeley, Department of Electrical Engineering and Computer Sciences Position ID: University of California, Berkeley -Department of Electrical Engineering and Computer
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research, teaching, and leadership skills. Candidates must possess excellent communication and interpersonal skills to work effectively in our team, as well as a willingness to learn new methods and
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spanning multiple diseases. About the lab: The Glastonbury Lab is focused on developing and applying Machine Learning to problems in digital pathology and spatial transcriptomics. The group has a particular
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for a postdoctoral role and how the proposed research fits with the research area of Dr. Haeok Lee (5 pages maximum) 4. A list of three references from individuals familiar with your scholarly and
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for an academic career are encouraged to apply. For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, statement of research interests and three letters
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machine learning models, natural language processing (NLP), and ontology-based frameworks to enhance simulation, curriculum development, and personalized learning in health professions education. Develop
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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decision-making for complex infrastructure systems. This position offers an opportunity to contribute to interdisciplinary research at the intersection of civil engineering, machine learning, and systems
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. Irradiated mechanical property prediction models and property correlation metamodels will be developed considering traditional and machine learning approaches. Extrapolation will be performed using a data
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methodologies generally, machine learning techniques, OR complexity analysis/nonlinear dynamics are particularly well-matched to the opportunity, but applicants with theoretical expertise related to compact