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Qualifications: Knowledge of kinetic modeling and/or machine learning interatomic potentials. Background Investigation Statement: Prior to hiring, the final candidate(s) must successfully pass a pre-employment
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Engineering, Biomedical Engineering (Medical Informatics), or related areas. Recipient category: Masters, enrolled in the course: Degree courses: enrolled in doctorate. Non-conferring degrees courses: enrolled
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(or equivalent) in Computer Science, Machine Learning, Mathematics, or a related technical field. For Postdoctoral Fellows: A completed PhD in one of the fields mentioned above and a strong publication record
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models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue samples. Requirements: PhD completed by
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the application of rock physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or
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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
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disciplines, including human-robot interaction, robot learning, soft robotics, computer vision, and agricultural robotics. About the PhD project: We are looking for a highly motivated and talented PhD research
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | about 1 month ago
: Electrotechnical and Computer Engineering. Admission requirements: Students enrolled in a PhD. program in Electrotechnical and Computer Engineering, or in related areas, or alternatively, an MSc degree in
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individual to join this exciting collaborative research program that builds upon existing strengths in ADRD biology and genetics (JAX) and bioinformatics methods and machine learning approaches (Roux
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Department of Computer Science of Faculty of Science invites applications for a DOCTORAL RESEARCHER IN MACHINE-LEARNING, STATISTICS AND DATA-CENTRIC ENGINEERING starting from November 2025, or as