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University of Tübingen Neuroscience student lab Careers Back Job vacancies IT & Library / Technology & Maintenance / Administration Professorships Postdocs, assistant professors, junior research group leaders
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equipment Opportunity to work in the highly interdisciplinary and exciting field of neuromorphic and brain-inspired computing, collaborating with physicists, neuroscientists, materials scientists, and
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profile: • Very good degree (Master or Diploma) in aerospace engineering, mechanical engineering, computer science or a comparable field. • Experience in machine elements, structural analysis, fault
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, chemistry, material science, chemical engineering or related disciplines Experience in the field of energy storage Knowledge of X-ray methods Experience with programming languages (ideally Python) Fluent in
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science foundation (DFG). Doctoral students (m/f/d) are facilitated to participate in the doctoral program in order to successfully complete their dissertation. We offer an attractive workplace with
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. Candidate´s profile: • Master’s degree in Life Sciences, in Computational Biology or MD degree • Previous research experience in immunology • Experience in flow cytometry, cell culture and in high-dimensional
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Humboldt Research Award programme information. Humboldt Research Award programme information (PDF, 63 KB) Recently selected award winners Hint Online info event: If you would like to learn more about this
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, chemistry, material science, chemical engineering, or related disciplines Knowledge of X-ray methods Experience in the field of energy storage Experience with programming languages (ideally Python) Fluent in
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Additive Manufacturing is looking for a full-time applicant as researcher (m/f/d) Qualifications and Experience Outstanding academic degree in computer science and engineering, materials science, metallurgy
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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling