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using data-driven approaches. You will be based in the Entrepreneurship and Innovation group—one of Sweden’s leading research and teaching environments—where you will collaborate with experienced faculty
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two pages) 2. CV 3. Diplomas of bachelor and Master level degrees 4. Bachelor/Master theses work/other relevant publications 5. Other merits of relevance for the position 6. Contact information to two
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credits Master’s degree thesis, or 15 credits Master’s degree thesis plus 15 credits Bachelor's degree thesis). Name and contact information of two professional references (note: letters of reference
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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of the numerical methods behind CFD and turbulence models. Experience in analyzing CFD data and interpreting simulation results. Excellent command of written and spoken English. Experience writing scientific reports
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scientific articles, reports, and presentations at conferences. Collaborating with researchers and stakeholders to collect data, discuss results, and organize workshops. Completing coursework required
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second-cycle studies at a university or higher education institution, two personal references, and knowledge of English. More information about the English language requirements can be found here: https
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- Knowledge and experience of fieldwork including sediment and water sampling For further information about a specific subject see; General curricula for the Board of the faculty of science and technology
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for gender equality and excellence . We celebrate diversity and consider equality and inclusion as fundamental aspects of all our activities. Discover more Find more general information about doctoral studies
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long-term, and most often global, perspectives on future renewable fuels for transport. We seek to rigorously analyse the feasibility of energy transitions, utilize empirical as well as estimated data