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the design and analysis of learning-enabled systems. At STAR, we tackle key questions like: - How can we build systems that are both intelligent and inherently trustworthy? - What methods ensure reliability
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. Project overview The project involves applying advanced statistical analysis, machine learning techniques, and modeling approaches such as agent-based modeling to analyze diverse climate and socioeconomic
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more appreciated and safer. About us In the Crash Analysis and Prevention team at the Vehicle Safety Division , Department of Mechanics and Maritime Sciences , we combine behavioral science, technology
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, medical analysis and treatment, material processing, etc. You will be given the opportunity to work in one of the world-leading groups in the area and combine device characterization with simulations
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Python and MATLAB Documented experience with analysis of complex scientific data e.g. through machine learning What you will do execute experimental tasks, such as planning of experiments alone or together
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applications, specifically targeting the prognosis and risk prediction of Heart Failure (HF) in patients. This research integrates AI safety, explainability, and multimodal medical data analysis to enhance
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University of Technology , specializes in the modeling, simulation, and analysis of tokamak plasmas. Our primary focus is on developing predictive models for turbulent transport in fusion-grade plasmas and
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and communicating research results verbally and in writing. The main tasks are to develop FSI algorithms for high-fidelity simulations, and conduct in-depth analysis to address aero-/hydro-elastic
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, including access to MC2 clean room and Chalmers Materials Analysis Laboratory (CMAL), as well as advanced laser facilities to steer research forward. Our specific mission is to innovate available
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thermal analysis (DSC, TGA). Additional experience in rheology, vibrational spectroscopy (IR, Raman), and X-ray diffraction (WAXS, SAXS) is a plus. Excellent collaboration skills, due