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. About You You will have a PhD in computer science, engineering, mathematics, or similar, strong programming skills, and experience with a contemporary machine-learning framework such as PyTorch. You will
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collaborating in the preparation and presentation of scientific reports and journal articles. You must hold a relevant PhD/DPhil (or be close to completion), together with relevant experience and should also have
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the results. You will work in an interdisciplinary team with several other research groups in Germany and abroad. Your Profile Completed PhD studies in physics, materials science or similar Excellent knowledge
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recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves
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experience). • Education: PhD or equivalent degree in mechanical engineering, physics, or applied mathematics or related disciplines. • Laboratory experience: mechanical and dynamical measurements, 3-D
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, Life Sciences and Medicine. Through its dual mission of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better
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collaborative neuroscience community across the University and actively engage in the interdisciplinary graduate program in Neuroscience and the undergraduate major in Neuroscience and Cognitive Science
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19 Sep 2026 Job Information Organisation/Company Karolinska Institutet (KI) Research Field Medical sciences » Medicine Researcher Profile First Stage Researcher (R1) Application Deadline 16 Oct 2026
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findings at national and international meetings, and to contribute to the supervision of PhD and Masters students. A PhD in Biochemistry, Molecular Biology, Chemistry, Bioengineering or a related discipline
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to independently develop reports and manuscripts and present findings in tabular, oral, written, and/or graphic formats. Minimum Qualifications PhD, MD or PhD/MD in Biological Sciences, Medicine, or relevant