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Field
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Your Profile: Basic qualifications: Completed Master’s degree with subsequent PhD in Physics, Chemistry, Material Science or related disciplines Experience with neutron spectroscopy (e.g. INS, QENS, NSE
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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dynamic, interdisciplinary, and international research community at the TUM Garching campus. TUM’s Department of Mathematics is part of the TUM School of Computation, Information and Technology (CIT
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Advanced software development and data analytics skills Hands-on mentality with first practical experience in developing innovative technology Inquisitive and passionate about research and knowledge transfer
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The project will require coding for data analysis and statistics, as well as NGS data analysis. Experience with either of these would be advantageous but an eagerness and commitment to learn is more important
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data synthesis. Their work will determine how urban features drive species diversity, how species diversity and urban features are represented in soundscapes and how these relate to human health and
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of Computation, Information and Technology (CIT), located on the Garching Campus, starting October 01, 2025 or later. The group is seeking a highly qualified candidate for a postdoctoral position who possesses
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Postdoc position: mechanisms of autoimmunity & autoinflammation in inborn errors of immunity (m/f/d)
the Excellence Cluster of Immunosensation2 in Germany (www.immunosensation.com). Requirements: PhD degree in life sciences (biology, biomedicine, immunology or comparable studies) Scientific background in
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The Professorship of Public Policy for the Green Transition (PPGT) focuses on designing and evaluating policies for the green transition worldwide. The group uses a variety of methods from automated data analyses
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. Severely disabled persons are given priority in the case of equal suitability. For further information, please contact Fr. Dr. Ekaterina Legchenko (ekaterina.legchenko@medma.uni-heidelberg.de ), phone +49