83 computer-science-intern "https:" "https:" "https:" "https:" uni jobs at Technical University of Munich
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depends on academic experience, family situation, tax classification, etc. · Generous funding for travel to and participation in international conferences, workshops, and summer/winter schools is available
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leader with a focus on data and AI Science to join us as soon as possible. Your qualifications PhD in Computer Science, Mathematics, Physics or related fields Experience in applied data science and machine
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to correct WDR45 mutations, assess molecular and functional outcomes, and explore off-target effects. Gain hands-on experience in cell culture, molecular biology, and advanced bioenergetics techniques, with
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03.08.2022, Academic staff The Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS) is a science and technology platform of TUM providing state-of-the-art proteomics, metabolomics and
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Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and
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the world) and present your work at top-notch conferences and journals in our domain. You should have completed your Master/Diploma studies with top grades in Computer Science, Artificial Intelligence
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grades) in a relevant field such as management, entrepreneurship, economics, (organizational) psychology, finance, or business informatics, • ideally has academic or practical experience in the field
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04.12.2025, Academic staff We are looking for an Independent junior research group leader (m/f/d) with knowledge of data / AI science to set up and lead the AI Core Unit of the BioSysteM Cluster
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04.05.2025, Academic staff We look for a motivated bioinformatician/computational scientist or postdoctoral candidate from the life sciences with experience in single-cell analyses who contributes
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integrating expertise from social sciences, humanities, and technical disciplines, the project will address critical issues such as explainability and fairness, ensuring LLMs contribute positively to education