57 algorithm-development-"University-of-Surrey" positions at Chalmers University of Technology in Sweden
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of the previous period, to complete the PhD studies. About SPACER SPACER aims to develop new architectures for porous electrodes to improve the power density and energy efficiency of redox flow batteries (RFB
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is being reshaped by technological developments. This PhD project will focus on investigating issues such as: How multimodal and AI-mediated practices shape knowledge construction How evolving
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beyond the Standard Model of particle physics to the interpretation of cosmological and astrophysical data on the origin, composition, and evolution of the universe. At present, our studies concentrate
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of the previous period, to complete the PhD studies. About SPACER SPACER aims to develop new architectures for porous electrodes to improve the power density and energy efficiency of redox flow batteries (RFB
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, are required. Important qualities are enthusiasm, to be able to drive and conclude projects independently, take own initiatives and discuss/develop own ideas, be creative and have a problem-solving mindset. The
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on-wafer characterization of high-frequency transistor devices, including bias-dependent S-parameters, pulsed I/V, and load-pull measurements Develop empirical device models that capture static, dynamic and
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description We are looking for a Research Specialist to provide advanced technical and methodological support in integrated photonics by developing and implementing experimental methods, maintaining and
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industry, academia, and government agencies. Our mission is to promote and integrate the life cycle perspective into all decision-making processes. We enable skills development and knowledge sharing among
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project focuses on developing and refining advanced organ-on-chip technologies to study and optimize nanoparticle-based delivery systems in biologically relevant environments. The project is strongly
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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites