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This postdoc project aims to address a critical challenge in quantum computing: errors in superconducting qubits caused by cosmic radiation, which cannot be corrected using existing methods
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different molecular libraries to examine their effect on the function of regulatory RNAs. Positive hits will then be further analyzed using in vitro translation, DMS MapSeq structural analysis, and other
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dynamical systems theory, including differential equations, simulation techniques, state-space and input-output representations, time-delay embedding, and/or time series analysis from experimental data
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-of-the-art cell and tumor biology methodologies, tissue analysis with histopathological techniques, and work with genetically engineered mouse models of cancer. Previous experience of conducting and analyzing
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applications, specifically targeting the prognosis and risk prediction of Heart Failure (HF) in patients. This research integrates AI safety, explainability, and multimodal medical data analysis to enhance
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programming skills and finite element (FE) analysis experience is a requirement. Knowledge of machine learning, Matlab and Abaqus is also highly desired. Previous experience with parametrization and automation
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workshops, collection and analysis of data, writing of scientific texts, participation in and leading funding applications and other tasks related to RoC's activities e.g. within the framework of CoP and the
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, proof assistants, term rewriting systems, optimizing compilers, program analysis tools, constraint solvers, or similar. Familiarity with linear algebra libraries and high-performance computing
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, Mathematica, Fortran, or other programming languages for data analysis and model implementation) are required. The candidate is expected to be capable and willing to independently initiate, conduct, and
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We are looking for a postdoctoral researcher to develop and implement tools for analysis of output from Bayesian inference under phylogenetic models About the position A postdoctoral researcher