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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
Summary About the Group: Our research group is dedicated to developing innovative datasets and modeling approaches to support drug development and regulatory evaluation. We focus on two major research areas
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Transport? Based in the Institute for Transport Studies at the University of Leeds, you will primarily contribute to the modelling and simulation of the integrated optimisation of Vehicle-to-Grid (V2G) energy
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students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental/School research
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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We are looking for a researcher, whose expertise lies in gravitational waves. They will be expected to conduct research on perturbative or nonperturbative waveform modelling, with applications
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computational modelling is a plus. The appointee should be organized, self-motivated and be able to work independently as well as in a team. He/she will work under the supervision of Professor Cora Lai in
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tunnel experiment to identify key influential factors. Once these parameters are identified, the research fellow will have the opportunity to contribute to the development of a control model based on
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the opportunity to work at the forefront of cardio-oncology science, combining sophisticated small animal radiation models, single-cell transcriptomics and state-of-the-art echocardiography. The successful
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the Sterne-Weiler Lab i n Computational Biology / Discovery Oncology. The postdoctoral position is focused on developing and applying foundational AI models to investigate clinically relevant cancer
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. Analyse and evaluate the performance of proposed methods under a range of scenarios, including worst-case and average-case models. Job Requirements PhD in Mathematics, Computer Science, or a closely related