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Field
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/careers. Qualifications MINIMUM QUALIFICATIONS Education ▪ Applicants are required to have (or receive before appointment) a PhD in a related field. Related Skills & Other Requirements ▪ Ability to develop
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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph
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, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation
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technologies, ethical implications, and governance frameworks, including knowledge of algorithmic accountability and transparency. Experience with both qualitative and quantitative research methods, and
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contribute to technical deliverables and help to plan for technology translation. Basic Qualifications PhD in engineering, biomechanics, or a related field. Additional Qualifications Interest in
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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Postdoctoral Fellow provides for an internship and continuation of scholarly activity and research after achieving the PhD or other doctoral degree under the direction of a senior faculty member who serves as a
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(CPS) for aquaculture, to sensors and platforms for maritime applications. The Postdoc’s primary task will be to lead the development of algorithm, software, and hardware to extend the current HAUCS
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algorithm development, data analysis and inference, and image analysis Ability to do original and outstanding research in computational biology, and expertise in computational methods, data analysis, software