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endeavours in AI have predominantly emerged from the domain of data science and mathematical engineering. At the same time, the deep penetration of AI into present-day science and technology creates challenges
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applications (e.g., to enable wearable robotics to proactively respond to the user’s activities). Deep learning has enabled promising results in various applications by automatically discovering complex
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the supervision of PhD students. You hold a PhD in (Medical) Physics, Engineering, Computer Science, Mathematics, Biomedical Sciences, or a related discipline. You have a track record in quantitative MRI (diffusion
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Job description:Title: DC14, PhD fellowship in law, “Legal Aspects of Open Science: FAIROmics as a Case Study”.Researcher profile: Doctoral candidate.Research field: Intellectual Property, Data Law
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sound enhancement (Siemens Industry Software NV, Müller BBM, Trèves, Phononic Vibes, Saint-Gobain Ecophon, Tyréns, Purifi ApS). Doctoral Candidate 2 (DC2) within VAMOR will develop novel deep learning
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Job description The Vandepoele research lab (Comparative Network Biology - https://www.vandepoelelab.be/ ) invites applications for a fully-funded PhD project for 1 year and extended with another 3
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to join a three-year research training within the EU-fundedMCSA doctoral network IN-DEEP. You will be hostedat Siemens in Leuven and be enrolled in the PhD program at KU Leuven. As a doctoralcandidate
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to acquire a deep understanding of her/his subject. Second, the network-wide training will be offered by the consortium during the whole project life cycle through 4 training schools and 3 workshops
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their performance and variability. One key parameter is carrier mobility which directly influences transistor performance and is impacted by defects and strain within the material. As PhD candidate, you
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LanguagesENGLISHLevelGood Additional Information Benefits The requirements for the position are: Obtained a PhD in a relevant field, and high quality publications Machine/deep learning algorithms. Biomedical data