391 machine-learning "https:" "https:" "https:" "https:" "https:" "VIETNAMESE GERMAN UNIVERSITY" uni jobs in Sweden
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Field
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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terms The Doctoral student positions are fully funded from start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five
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the world. More information about the Department can be found here: http://www.pcr.uu.se . We are seeking an internationally recognized scholar who is interested to contribute to further developing
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computational methodologies, ranging from atomistic and electronic-structure–based materials modeling and characterization, via machine-learning and high-throughput methods, to ab initio calculation
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generative machine learning models to create an active learning cycle to identify materials with adequate properties. Promising materials will be synthesized, characterized and evaluated in lab. This will help
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international academic institutions and 14 industry partners (https://euraxess.ec.europa.eu/jobs/401249 ). We work together in the field of fluid-structure interaction in technical systems and industrial
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well as online data collection (experiments, surveys). Expertise in advanced machine learning techniques and large language models (LLMs) —including web scraping, text mining, and neural networks—is considered a
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doctoral degree. More about being a doctoral student at LTH on lth.se. https://www.lth.se/english/study-at-lth/phd-studies/ Subject and project description ELLIIT (https://elliit.se ) is a strategic research
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of advancing Swedish academia and industry to the forefront of quantum technology, and to build a Swedish quantum computer. The student contributes to this project to explore fundamental and applied questions in
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in Lund and be part of CREATE Health and Lund University's Cancer Center . Subject description The project aims to increase the understanding of the biology associated with response to CAR T-cell