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Field
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: Dynamical Systems Control Theory Formal Methods Reachability Analysis Computational Geometry Context The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/cps/members
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molecular/condensed matter physics) and the developments on new tools in perturbation theory and in computational methods (gradient flow), including quantum computing. We look for ambitious candidates with a
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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biology, biochemistry, nutritional sciences or another biological/medical field Expertise in chronobiology and circadian rhythms analysis Experience in general molecular and cell biology methods Experience
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and interest in one of the following fields: • Solid state quantum information science. • Quantum optical properties solid-state systems (e.g. semiconductor quantum dots, colour centers in wice gap
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strategies. We develop new methods with which tumors can be diagnosed more precisely and cancer patients can be treated more successfully. Every contribution counts – whether in research, administration
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innate immune responses. Our group uses a wide range of experimental methods, including multiparameter flow cytometry, single cell gene expression analysis and in vitro culture systems, including 3D human
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of targeted therapies. Analyzing high-dimensional single-cell data has its own statistical and computational challenges, and standard tools often cannot be applied. The purpose of the position and goal
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products (1D and 2D NMR, HRMS, other spectroscopic and computational methods) Experience in writing first author-publications, high publication track record in scientific journals and conference
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and to identify new therapeutic targets and prognostic biomarkers. Novel data integration methods allow to identify signatures of retinal cell types in liquid biopsies without the need for a direct