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! The Clinic focuses on inflammatory diseases of the central nervous system, especially multiple sclerosis. As part of the Department of Neurology, we study the pathogenesis and treatment of this and other
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for Infectious Diseases Research. This position will be responsible for performing various duties necessary to further research on multiple grants. Responsibilities: Responsibilities will include developing
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Technology of China (UESTC) Multiple postdoctoral positions are available at the Institute of Fundamental and Frontier Science (IFFS), University of Electronic Science and Technology China (UESTC) located in
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conditions, identification of vulnerabilities, and development of resilience enhancement strategies. Contribute to the design, development, and implementation of new models, methods, and algorithms
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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collaboration in optimising data analysis algorithms for the raw detector data, including improving position reconstruction and pulse-shape discrimination algorithms which can be implemented on in the front-end
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) and developing meaningful scaled score formulas and metrics. The post-doctoral associate will support multiple aspects of this work, including conceptualization and design of the scale scores, computing
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, especially in the field of optoelectronics; Experience in programming languages such as C++, Python, LabVIEW, IGOR, or MATLAB for data analysis and algorithm development; -Experience with simultaneously
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | about 1 month ago
of multiple timescales. Collectively induced stochastic resonance phenomena on molecular ensembles in optical cavities. Cavity-induced off-equilibrium consequences on chemical reaction rates Develop (ab-initio
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted