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outputs in lidar technology and real-time wind-field reconstruction. Expert in wind turbine response analysis. HAWC2 user expert. Demonstrated expertise in data analysis and signal processing with large
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, glacier speedup, and ice-ocean interaction. Candidates will work with satellite altimetry, velocity datasets, and climate data to quantify ice sheet mass balance and dynamics. Applicants should hold a PhD
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in
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systems with a view to applications for quantum computing. .. The successful candidate is likely to have some of the following qualifications: A PhD in Physics, Chemistry, or a related discipline
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. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in
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well as abroad. Your primary tasks will be to: Using automotive lidars for detection of wind turbine blade deflection Development of efficient ways to analyze the automotive lidar data Develop the technology to
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and societal impact. The Department of Electronic Systems employs more than 200 people, of which about 90 are PhD students, and about 40 % of all employees are internationals. In total, it has more than
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application form, and attach all your materials in English in one PDF file. The file must include: Application (cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications Contact information
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work in close collaboration with a large, interdisciplinary team of quantum scientists, engineers, and biomedical researchers. Your key responsibilities will be to: Conduct research that will bridge
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position is for 24 months, with a starting date on February 1, 2026 or soon thereafter. The Postdoc Fellow will analyze the evolution of the total income distribution for a large sample of firms in