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Field
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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analysis. Experience in formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral communication skills in German are desirable
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motivated candidate with a strong mathematical background, particularly in one or several of the following areas: multivariable control, nonlinear control, robust control, matrix analysis, and convex
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/College research strategy. 2. Document research output including analysis and interpretation of all data, maintaining records and databases, drafting technical/progress reports and papers as appropriate. 3
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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in statistical analysis, quantitative methods, or mathematical modelling obtained outside these subject areas may also be included. The requirements do not need to be fulfilled at the time of
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in thermodynamics, optimization, and control theory. Strong understanding of mathematical modeling, numerical optimization, and/or model predictive control (MPC). Experience working with large-scale
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This project provides an excellent opportunity to develop state-of-the-art mathematical models and computational tools of emerging respiratory pathogens, within a world-renowned research group
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Immonuprecipitation (ChIP); Genome editing, e.g. to (degron) tag proteins of interest; Bioinformatic analysis of generated sequencing data. During your PhD, you will learn about the field of gene regulation, expand our
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites