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Field
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health and disease under the direct supervision of Dr. Jonathan Kirk. Minimum Education and/or Work Experience M.D. or PhD Required Qualifications Certificates/Credentials/Licenses NA Computer Skills
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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Sciences, who develop, manage, and refine machine learning techniques for identifying copyists; Participation in the dissemination of research results through presentations and publications; Data management
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or commensurate with experience Type of Position Student Position Time Status Full-Time Required Education PhD or MD Required Related Experience Biomedical Sciences Required License/Registration/Certification NA
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backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate closely with experimental scientists and contribute
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performs MRI research and development of advanced multiparametric methods for the evaluation of primary and metastatic brain tumors. Recent work incorporates machine learning methods to advance
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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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analyzing urban data (traffic, energy consumption, environment). Strong skills in integrating IoT devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence
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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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and the terms of the research grant when extending an offer. Completion of PhD in Data Science, Computer Science, Mathematics, or other discipline aligned with CDS faculty research by the start date