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Field
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prediction algorithm and molecular dynamics simulations. For more details, please view https://www.huilingshaogroup.com/. We are looking for a Postdoctoral Research Fellow to design and execute independent and
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objective of the project is to develop knowledge, models, and algorithms for physics‑informed autonomous control of heavy machinery in uneven and deformable terrain. Specific project tasks include fundamental
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market mechanisms. The successful candidate will work closely with colleagues across the project to develop analytical methods, algorithms, and visualisation tools that connect IoT monitoring with broader
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algorithms for mining molecular multi-omics and medical data to improve multiple tasks of precision medicine and discover new precision therapeutics. The successful candidates will work closely with our
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will help design and build novel systems and algorithms that challenge traditional assumptions in databases, guided by both real-world needs and formal foundations. They will work at the intersection
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foundations, focusing on the structure and complexity of quantum computational models; (ii) optimization and related graph-theoretic methods, using polyhedral geometry and algorithmic optimization (e.g., vertex
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leading role in developing and implementing predictive algorithms designed to identify those most at risk from extreme heat, as well as offering personalized adaptation advice --- translating rich multi
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to polymer-fluid coupling. Further areas of interest include numerical algorithms for high-dim. problems, classical (mainly finite elements, FEM) as well as alternative discr. meth. (e.g., Lattice Boltzmann
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pipelines for large-scale scattering datasets. Participate in synchrotron experiments at APS beamlines to generate datasets that support algorithm development and validation. Work closely with ISAAC
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strategies, and control algorithms • Strong knowledge of power electronics, drives, and control is highly preferred. Experience with hardware testing and real-time simulation will be advantageous