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on using unstructured and overset meshes with high-fidelity algorithms to obtain scale-resolved data. Candidate will also post-process data using data-driven and physics-driven methods to extract fundamental
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, physics, or a medical imaging related field. Experience with developing advanced pulse sequences or accelerated acquisition and reconstruction algorithms will be highly valued. Interested candidates should
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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: variational formulation of neural network learning convergence of Langevin Monte Carlo algorithms Dissemination of research results through participation in scientific conferences, presentations, and
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for these polymers and implement computational algorithms to assist their optimization. The RISE Polymer Lab is dedicated to developing the next generation of robust, intelligent, sustainable, and evolving (RISE
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construction machinery to improve efficiency, adaptability, and safety under varying operating conditions. The work will involve designing and prototyping intelligent control algorithms, developing runtime
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the world are tackling global issues and making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in
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efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks represented as tensors. Investigate different
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include experiments carried out at the Francis Crick Institute in Mishto lab. About the role: The post aims to identify HLA-I epitopes and validate them with different techniques. The successful candidate
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Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum experiments and quantum algorithms for computational geometry problems. Prior