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Field
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: - Quantum computing with qudits, quantum error correction and fault-tolerance - Quantum optics of trapped ions and Rydberg atom arrays - Numerical tensor network techniques - Topological order and (de
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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cells to generate advanced model systems for studying beta-cell maturation and failure. You will apply state-of-the-art molecular biology and tissue culture methods, along with next-generation sequencing
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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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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