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research team led by Dr. Michael Stolpe and the doctoral program of the interdisciplinary Research Alliance Leibniz INFECTIONS. The group cooperates closely with leading medical researchers, biologists and
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phases Your profile Excellent Master’s or Diploma degree in medical physics, physics, computer science, medical engineering or a closely related field with a strong interest in data science and
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on conferences and in publications Requirements Master’s degree in physics or chemistry, computer science or equivalent Interest in Physics and Machine Learning Good written and spoken English Ability to work both
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at the intersection of molecular life sciences and computational sciences. This program offers comprehensive perspectives and mentorship in both experimental and computational fields, catering to graduates in molecular
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. This joint research project is organized as an interdisciplinary graduate school, combining individual supervision with intensive collaboration across institutions. The structured qualification program
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their supervisors at the beginning of the programme. Application Guidelines The application deadline for the winter term 2026/2027 is December 31, 2025. Applications may be submitted in German or English
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areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics Familiarity with
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molecular tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries
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at renowned institutions, including the Max Planck Institute for Infection Biology, German Rheumatology Research Center (DRFZ), Charité-Universitätsmedizin Berlin and Technische Universität Berlin
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. Qualifications: • Completed academic university degree (Master level) in mathematics, computer sciences, physics or a related discipline • Knowledge of programming, machine learning methods, mechanistic modelling