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algorithmic aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by
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specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in the computational biology and
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two post docs and MSc + BSc project students) studying how microbe-host interactions affect host health, in an Evolutionary Medicine framework. We focus on Helicobacter pylori, an ancient inhabitant
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by: Developing specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in
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investigate new algorithmic principles that make learning agents adapt to non-stationary environments in an autonomous manner. The expected outcomes are new theoretical insights about the algorithmic roots
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is to develop machine-learning-based algorithms for transmitter pre-distortion and receiver post-distortion architectures that enable distortion-free quantum communication systems. A key focus will be
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is an advantage but is not required. A strong interest in evolutionary principles, ecological principles, and data science are expected. The applicant must be interested in working in
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algorithmic solution development. The group focuses particularly on automated decision-making in autonomous cyber-physical systems, combining mathematical optimization, machine learning, and decision theory
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work at the intersection of palaeogenomics, bioinformatics, and evolutionary biology to overcome long-standing barriers in analysing degraded or low-quality DNA, enabling reliable genomic inference
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving