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decarbonization challenges at regional, national, and international levels. For more information about SDU LCE, please visit www.sdu.dk/lifecycle . Qualifications We are seeking a candidate with a master’s degree
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attention. We ask what can be done with experimental lab data in cases with variations of anisotropy. In addition to research tasks, you will take courses for 30 ECTS and both general and specific topics, and
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collaboration with staff scientists in the team - publish scientific articles based on the data you generate - present research findings at research meetings and conferences Your profile: We seek candidates
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., cloning) and/or genome engineering Experience with mammalian cell culture (cell lines; experience with primary immune cells is an advantage) Experience with Programming/data analysis skills Interest NGS
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characterization, dual-comb applications, numerical simulations, and data analysis. You will play a leading role in disseminating research results and actively participate in collaborative projects. You will also
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using signal changes to learn about the weather and take appropriate action. By combining AI with physics and real-time data, the project improves weather forecasts and makes communication systems more
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central role in SDU’s ambition to be a national and European hub for semiconductor and chip innovation. Further information For further information about the position, please contact Professor Farshad
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of machine learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics
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enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education
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(SNSPD). Additional responsibilities include developing efficient coupling of free-space optics to optical fibers, conducting extended data-taking runs with TES and SNSPD systems, and performing data