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modelling and machine learning to join and lead a dynamic international team of early-career researchers. This exciting role is part of a cutting-edge project investigating the structural integrity
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, and utilize the state-of-the-art multi-scale atmospheric models, along with measurement and statistical approaches, to understand the mechanisms that drive the climate-air quality interactions, and
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these influence immune function and disease. The project combines biochemistry, molecular and cellular biology, and in vivo models to deliver a comprehensive picture of immuno-metabolic function during inflammation
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the management of large datasets (in the excess of 21,000 data points) and advanced data analyses, including Hierarchical Linear Modelling and Growth Modelling. Additional responsibilities include providing drafts
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environment experts and researchers that will be focused on developing heat health prediction and thermo-physiological models. The main areas of responsibilities of the role will include: Working closely with
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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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forward the use of phase field models in earthquake rupture dynamics and fluid-driven fracture processes. The project bridges applied geophysics and computational mechanics, and is jointly developed with
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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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, 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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 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