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the Research Group “ Numerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting September 1, 2025. The position is assigned to the research project "Randomization of Surrogates
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Master’s Student (m/f/d) – Thesis The Leibniz Institute for Food Systems Biology at the Technical University of Munich (LeibnizLSB@TUM), a legal foundation under civil law based in Freising, is a prominent member of the Leibniz Association. Our institute integrates cutting-edge biomolecular...
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master's degree in agricultural or environmental economics, applied mathematics, or a related field Good background in bio-economic modelling, CGE modelling, and optimization techniques Experience with
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a doctorate. We are looking for: candidates with a Master’s degree in mathematics or a closely related field and with a strong background in probability theory. Prior knowledge in spatial stochastic
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theoretical ecology, geosciences, applied mathematics, environmental physics, or a related field. Research experience in numerical modelling, preferably with knowledge of either eco-evolutionary models and/or
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related field Doctorate optional Experience with bioanalytical methods (mass spectrometry, flow cytometry) Strong affinity for numbers and mathematics as well as a keen logical understanding Keen interest
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, Regional Science, Economic/Quantitative Geography, or Mathematics knowledge and experience in spatial equilibrium modeling (e.g., through coursework, thesis work, or previous projects) is beneficial
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master's or diploma degree in computer science or mathematics already successfully completed doctorate confident demeanor and proficient use of German and English (both equivalent to at least B2) expertise
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The mission of the Leibniz Centre for Agricultural Landscape Research (ZALF) as a nationally and internationally active research institute is to deliver solutions for an ecologically, economically and socially sustainable agriculture – together with society. ZALF is a member of the Leibniz...
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from models. Your Qualifications / Experience: • A Bachelor or Master in computer sciences, engineering, physics, mathematics, or a related discipline • Work experience in data management and scientific