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Field
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algorithms in the context of the ERC WINC project (www.winc-project.eu ). Functions to be developed: Study recent trends in the field of quantum computing for communications and computing. Analyze limitations
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. · Developing and implementing computationally intensive algorithms using high-performance computing (HPC) clusters. · Managing and analyzing multiple large-scale datasets, including UK Biobank (UKBB
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Equation, Stochastic simulation algorithms, and approximation methods. ● Experience with single-cell or spatial transcriptomic data analysis. ● Familiarity with machine learning and deep learning
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-age-gap prediction algorithms applicable to Asian populations by integrating large-scale plasma proteomic datasets generated using the Olink and SomaScan platforms. The organ age gap is defined as the
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programming, microfluidics, and engineering to design sophisticated algorithms for exploring and manipulating information encoded in DNA-based graphs. The position is fully funded by a prestigious CNRS
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computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus. ● Ability to work independently as well as part of an interdisciplinary team in a
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, etc. - ML-augmented numerical method development. - High-performance computing (HPC). - Quantum algorithm design. - Error correction or error mitigation. City
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, including prediabetes, type 1 and 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). Their research informs artificial pancreas algorithms and contributes to drug development targeting hepatic
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algorithms, and some knowledge of data science and machine learning (through coursework, self-learning, or personal projects). The selected student will work with Ph.D. and master's students to help develop
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. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python