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clinical research with an emphasis on novel technology development. Why should I apply? Under the guidance of a mentor, you will learn and gain hands-on experience to complement your education and support
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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably
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Publish high-impact research in leading journals and present findings at international conferences on energy systems and machine learning Collaborate with industry partner to tackle challenges of practical
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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or equivalent Skills/Qualifications Technical Skills: Programming and integration of machine learning algorithms, reinforcement learning and symbolic planning in real robotic platforms. User modeling techniques
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through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated communities in South Carolina and
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for a dedicated PhD student to join our team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In
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/en/available-jobs/job/294737/phd-research-fellow-in-reinforcement-learning-for-generative-systems-in-physics-at-the-inted-center Where to apply Website https://www.jobbnorge.no/en/available-jobs/job
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. You have: A PhD in Computer Science, Machine Learning, Applied Mathematics, Scientific Computing, Data Engineering, or a closely related field. Demonstrated ability to conduct high-quality academic