209 application-programming-android-"Prof" positions at Technical University of Munich
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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field
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behavior planning, control) -Very good programming skills (e.g. Python) -A conscientious and independent way of working -High motivation and commitment -Negotiation skills in written and spoken German and
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, control) -Very good programming skills (e.g. Python) -A conscientious and independent way of working -High motivation and commitment -Negotiation skills in written and spoken German and English What we
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of your BSc/MSc theses, via email to: dss@in.tum.de As an equal opportunity employer, TUM explicitly encourages applications from women and all others who would bring additional diversity dimensions
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programming skills in a higher programming language (e.g., Python, Java). You already work with traffic simulations and digital twins, or they spark your interest. You break down complex topics by approaching
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of metrology for environmental applications, and monitoring greenhouse gas and pollutant emissions using atmospheric measurements and dispersion models. We are looking to grow our team from June 2022 onwards
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08.04.2022, Wissenschaftliches Personal Development of Lattice-Boltzmann solver, programming in C/C++ and CUDA, implementation on GPU cluster, testing of real-time capable software on flight
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study the degradation/evolution of the sensor chemistries under operating conditions. Qualified applicants must have: • A master's degree/PhD in chemistry, chemical engineering, materials science, or
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-LIKE1 suppress overbending during negative hypocotyl gravitropic growth. bioRxiv 2024.2005.2024.595653 The position is suitable for disabled persons. Disabled applicants will be given preference in case
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application to the European mission of a Digital Twin Earth. ML research directions will include physics-aware machine learning, reasoning, uncertainty estimation, Explainable AI, Sparse Labels and