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Field
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to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
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Physical Oceanography and Instrumentation, Marine Chemistry, Biological Oceanography, Marine Geosciences, and Marine Observations works interdisciplinary within a joint research program. What will be your
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several students from abroad in our master’s program each year. It is important to us to provide a family-friendly environment at ESAGA. The university has several offers regarding child care for children
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, Computer Science or related fields (for PhD); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC
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Extensive knowledge of X-ray methods Knowledge of synchrotron science Knowledge of catalysis Experience in energy storage Experience with programming languages (ideally Python) Fluent in written and spoken
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(MPPT). Your profile: We are looking for motivated individuals (m/f/div) with a Ph.D. degree in Electrical Engineering, Materials Science, Physics, or a related field. Candidates should have a proven
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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for laboratory and field work Strong background in programming and data analysis (preferably Python) Excellent data analysis and publication capabilities Excellent communication skills in English, both written 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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fields Interest in immunology, systems biology and translational research Strong interest in mass spectrometry-based proteomics (prior experience advantageous) Proficiency in computational data analysis