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groundbreaking research. The project is devoted to learning-based control for high-dimensional data. Application to individually optimized immunotherapy for cancer will also be considered. The grant covers two
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of the position is to develop the independence as a researcher and to create the opportunity of further development. The research tasks include the optimization of cultivation processes and freeze-drying
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dynamics, such as hidden Markov models or statistical jump models, affect the optimal decision-making process for an investor. Specifically, we aim to develop new methods for regime models, including
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consists of 18 research groups covering a wide range of mathematical disciplines – from pure and applied mathematics to numerical analysis and optimization, as well as mathematical statistics and machine
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maximal signal-to-noise and detection of picomolar levels of protein in the blood. The laboratory’s part of the project is to test and optimize this new strategy and subsequently use it to evaluate