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new standards in computational metabolomics – facilitating biomarker discovery, advancing personalized health monitoring, and improving clinical decision-making. The work will be carried out under close
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Master’s degree in biotechnology, bioengineering, bioeconomy cell biology, molecular biology, or a comparable field of study, preferably with a background in life cycle assessment (LCA) and techno-economic
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in Life Sciences or in Computational Biology • Experience in flow cytometry, cell culture and in high-dimensional single-cell data analysis and programming skills are a plus • Organizational skills and
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or comparable degree in biology, physics or a related discipline. You have experience in quantitative biology, experimental soft matter, or experimental biophysics. You enjoy working in interdisciplinary and
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candidate, you have an outstanding Master's degree or comparable degree in biology, physics, applied mathematics or related disciplines. As an experimental candidate you have experience in biological systems
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• Scientific publishing Your qualifications: • Completed academic university degree (university diploma / M.Sc.) in Computer Science, Geoscience, Physics, Data Science, or comparable subjects • Experience in
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at start: • Strong background in T cell biology/immunology. • Hands-on experience with transgenic mouse models, including breeding and colony management. • Proficiency in preparing and processing lymphoid
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, Mathematical modelling, Biology, Environmental Science, Physical Geography, or related fields. • Specific research in agricultural-environmental disciplines, and particularly with respect to livestock
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the courses Advanced Mathematics 1–2 and/or Statistics at the TUM Campus Straubing. Your profile: Above average master’s degree in mathematics or (theoretical) computer science with a focus on discrete
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output. More information about the group is available at www.ep.mgt.tum.de/pur Application Please send a cover letter that explains how this position fits with your experiences and goals, your curriculum