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University of Science and Technology (NTNU) has a vacant position as PhD candidate in the field of machine learning for materials science. Your immediate leader will be the Head of Department. About the
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, calorimetry, and synchrotron experimental measurement techniques. Knowledge of AI-based and machine-learning methods is also beneficial. For further information about a specific subject see General syllabus
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complex data sets Clear oral and written presentation skills, with the ability to communicate with both academic and policy audiences Desirable Criteria: PhD in Health Economics or Economics Evidence of
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technology and method development, and brain-machine interface research. Exceptional candidates from other neuroscience areas are also encouraged to apply. Learn more about our institute and these
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internationally through conferences, seminars, and workshops. Translate findings for diverse audiences while maintaining scientific rigor. Qualifications: PhD in artificial intelligence, machine learning
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development, and machine learning. The ideal candidate would conduct highly collaborative dry lab research in areas of focus aligned with departmental strengths in learning and memory, decision making, motor
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of reactive force field molecular simulations, supervised machine learning techniques and understanding of mass spectrometry techniques. The post is available for 3 years from 1 September 2026. If you are still
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connected to the university's M-TRAC translational research program. Required Qualifications* PhD in Electrical & Computer Engineering 1 or more years of relevant postdoctoral research experience Modes
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Job description QuTech, the research center of Delft University of Technology (TU Delft) is hiring for a Doctoral Candidate (PhD) position in partnership with the Questing Doctoral Network
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First Stage Researcher (R1) Positions PhD Positions Application Deadline 8 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Is the job funded through the EU