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Field
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Project Background: Why some people with multiple sclerosis (MS) experience faster changes in brain structures (neurodegeneration) than others? What genetic associations with brain regional
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rewiring in glioma. We will leverage our expertise in genetic engineering and m6A profiling, and characterize the specific metabolome and lipidome composition of glioma. We will assess the impact of m6A
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
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the project, including archaeology, palynology, archaeobotany, ichtyoarchaeology and sediment genetics. The candidate will obtain the PhD by publishing several articles in peer-reviewed academic journals.
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control engineering, optimization algorithms Control of drones and flight experiments as well as knowledge in AI / Machine Learning would be an asset Outstanding academic records Teamworking experience, e.g
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control