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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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& BIOCHEMISTRY Location Code CHEMISTRY & BIOCHEMISTRY (02113A) Is this split and/or fully grant funded? Yes Duties and Responsibilities As a postdoctoral scholar at Dr. Pengfei Li’s lab, you will play an important
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Physics or an adjacent field, such as Mathematics, completed by the start of the appointment Knowledge of High Energy Theory and Machine Learning, as usually acquired through a PhD in Physics or a related
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experience will be valued. Proven expertise and experience in computational statistics, machine learning, programming in R and/or Python, the development of methodological procedures, and the implementation
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. The position combines Empa UESL’s expertise in developing and accessing energy system models with the methodological expertise of the IMOS Laboratory in machine learning and foundation models. Postdoctoral
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biostatistics group). The department is situated at campus Solna. Further information can be found at http://ki.se/en/meb The KI Psychiatric Genomics Institute (KI-PGI) at MEB is seeking 1-2 postdoctoral
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Glimpse of the Job The Postdoctoral Research Associate will perform independent research activities requiring an advanced level of knowledge in a field of science or learning. This work is predominantly
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top-tier venues and will have dedicated time for advancing their own research. The project is in collaboration with CCL (The Center for Connected Learning and Computer-based Modeling, PI Uri Wilensky
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perspectives including computational or machine learning. The successful applicant can expect a highly competitive level of support for the start-up of their research program. Considerable institutional
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characterization (PXRD and Rietveld refinement, SEM, XPS, etc) Experience with machine learning techniques, particularly machine-learned interatomic potentials, in the context of chemical research. Programming