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an interdisciplinary research environment aimed at achieving a comprehensive understanding of geomagnetic field evolution across different timescales, including both stable and extreme periods. This will involve working
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collaboration across the Berlin biomedical research hub. Job Description investigate mechanisms that maintain and diversify genome stability analyze context-dependent DNA repair processes across different cell
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priming and susceptibility to infections. The project aims at understanding how endogenous nucleic acids can contribute to the basal activation of innate sensors. Our group previously studied the role
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. We benefit from the different expertise, perspectives and personalities of our staff and welcome every application from qualified candidates, irrespective of age, gender, ethnic or cultural origin
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to consider the Ericksen—Leslie model with stochastic fluctuations and investigate it in terms of existence of solutions and their approximation, the associated large deviation principle and the simulation
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priming and susceptibility to infections. The project aims at understanding how endogenous nucleic acids can contribute to the basal activation of innate sensors. Our group previously studied the role
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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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adsorption of guest molecules in the pores, ionic conductivity and (opto-) electronic properties of these functional films as well as their applications, e.g. for molecular separation and as unique sensors
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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algorithmic algebra. For more information about the TUM Department of Mathematics, please visit our website: https://www.math.cit.tum.de/en/math/home/. The position is a full-time position (100%), initially