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research infrastructure Development of process models, process engineering approaches, and process control strategies for injection molding and extrusion Further development of inline-capable process
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model for innovative medical education and a centre for transformative research. The School’s primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised
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engineering? Then this professor position might be for you. We are looking for a new professor to lead research in probabilistic machine learning, with a focus on areas such as deep generative models, Bayesian
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the top 10% of their class in MSc and BSc, and have exceptional grades; should have a background in microwave engineering and machine learning; should have strong communication skills and be fluent in
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numerical approach The PhD is part of a Franco-German co-funded project between IFP Energies Nouvelles (IFPEN) at Lyon and the Hamburg University of Technology (TUHH), focusing on the modelling of gas/liquid
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Description In this project, we develop machine learning models for prediction of optical properties of chiral molecules based on DFT/CCSD data which we calculate ourselves. We include derivative information by
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scenarios and time series analysis for groundwater modelling. Fluent command of English for scientific writing and international collaboration. Ability to work effectively in an international research team
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Materials, Biomaterials, Energy Materials, Semiconductor Materials, Nanomaterials, and Computational Modeling of Materials. Expertise in experimental synthesis and characterisation or advanced computational
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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department in the ISSA expertise center that develops advanced AI solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid