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. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in R and/or
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public health. Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, Bayesian methods, deep learning). Is an experienced programmer in
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Electrical Power Engineering and Mechatronics. The Proposed PhD thesis topic: “ AI-Driven Battery Life Optimization for V2X-Enabled Software-Defined Vehicles ” Supervisors: Sup. Researcher Dr. Hadi Ashraf Raja
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» Earth science Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Estonia Application Deadline 31 Jan 2026 - 23:59 (Europe/Tallinn) Type of Contract Temporary Job
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Environmental science » Earth science Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Estonia Application Deadline 31 Jan 2026 - 23:59 (Europe/Tallinn) Type of Contract
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Research Infrastructure? No Offer Description Tallinn University of Technology School of Science, Department of Cybernetics offers a 4-year PhD position in Applied Physics and Mathematics. The Proposed PhD
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Have you always wondered how neural models process information? Are you
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Technology. This interdisciplinary lab will include two PhD students and a cross-disciplinary team of supervisors. The team members, including the two PhD students, will collaborate closely to bridge technical
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Package 3 (Trustworthy Data and Models) of the EU Horizon ENDOTRAIN doctoral training network. The recipient of this PhD position will carry out research activity at the Department of Computer science
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» Industrial engineering Engineering » Systems engineering Computer science » Digital systems Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 31 Jan