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outline your general research interests. The position will remain open until it is filled. Selected Publications: 1) R. Kürsten, J. Mihatsch, T. Ihle, Emergent flocking in mixtures of antialigning self
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., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted in the Department of Microbiome Dynamics of Prof. Gianni Panagiotou of the Leibniz-HKI in
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, excellent analytical skills experience in research software engineering, programming experience (e.g. R, GAMS) active interest in energy systems analysis and climate change mitigation We expect the ability
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, excellent analytical skills experience in research software engineering, programming experience (e.g. R, GAMS) active interest in energy systems analysis and climate change mitigation We expect: the ability
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references Interested applicants should send us the necessary documents via email to: applications@msrm.tum.de quoting “PhD/Postdoc Application, Project R” in the e-mail subject line. Applications will be
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience
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, R/Python) is welcome We offer: A dynamic, interdisciplinary service platform environment embedded in Germany’s leading Life-Science campus Access to cutting-edge instrumentation (timsTOF fleX MALDI-2
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort
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literacy with at least basic programming skills (R, Python). Analytical mindset, with a keen interest in advancing proteomic methodologies Knowledge of cancer biology is an advantage We offer Cutting-edge