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requirements: • PhD diploma in related field • Excellent skills in statistical analysis • Very good knowledge of English; spoken German is a benefit • Excellent scientific and writing skills Who we are: You will
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part of a degree program. In particular, knowledge about finite-element analysis is an absolute must . Familiarity with iterative solvers , preconditioners , multigrid methods , and mixed-precision
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advanced wet-lab experience in molecular biology and in reverse genetic approaches. • You are familiar with FAIR data handling and in silico data analysis. • You work precisely and reliable. YOU FIT TO US
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• Information-theoretical analysis of entanglement-supported classical communication, • Encoding protocols for entanglement-assisted classical communication, • Protocols for interleaving transmission in networks
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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- Experience in RNA-sequencing and bio-informatic analysis is a plus - Flexible team player We are offering excellent research conditions, a highly motivated and interdisciplinary team, a friendly working
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
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: - QUANTITATIVE VERIFICATION: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification