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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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. With over 26,000 students and more than 4000 scientists, research, teaching, and learning dedicated to the advancement of science and technology have been conducted here for more than 200 years, guided
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genomic, gene expression and gene regulatory network data sets. We are looking for a highly motivated scientist to work in a dynamic and interdisciplinary academic team focusing on different aspects
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and medical image analysis. The interdisciplinary and collaborative research environment at the DKFZ also results in excellent opportunities for computational and data scientists with interest in
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devices. The project will involve significant collaboration, sample exchange, semiconductor and device characterisation. For more information on the position please contact Prof. Phil Dale or Prof. Alex
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case studies exploring migration trajectories Collaborate with interdisciplinary teams, including historians, data scientists, and archivists Participate in the dissemination of research through academic
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ecosystem of experienced entrepreneurs, distinguished scientists, and industry leaders. This collaborative environment encourages cross-pollination of ideas, mentoring opportunities, and strategic
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Junior Research Group in the field of Metabolic Plasticity. What we are looking for in applicants: We are looking for established scientists in an early career phase (up to 6 years post-PhD) who
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biopsies and advanced, preclinical models. A combination of wet-lab and computational biology, close ties to the clinic, and a wonderful team of early career scientists give us the agility and expertise
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. The research group led by Martin Enge is specialized in methodology-driven analysis of patient data, especially in the field of single-cell multiomics. We are a multidisciplinary group with expertise in both dry