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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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operational constraints and employee preferences, within rigorous optimization frameworks. Data science and machine learning: experience with data preparation, feature extraction, and preference learning
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modelling, multimodal neuro-imaging and physics-informed machine learning to improve assessment of glioblastoma treatment response. The candidate will also be expected to contribute to the formulation and
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to machine learning and AI projects for satellite systems. We are looking for a candidate capable of developing ML models and optimization algorithms specifically designed for highly dynamic satellite
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/hacohen19a.pdf [4] Roh et al., FairBatch: Batch Selection for Model Fairness — https://arxiv.org/pdf/2012.01696 [5] Ren et al., Learning to Reweight Examples for Robust Deep Learning — https://arxiv.org/pdf
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 17 days ago
AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models to uncover how gene expression and mechanical forces interact
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and have synergiccollaborationeffects. Weexpect a motivatedearlycareer researcher with stronginterest and experience with GIS/earth observation/climateprojection data as well as machine learning models
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participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing. UConn has a vibrant
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advanced analytical and statistical techniques to extract actionable insights from complex datasets. Train, evaluate, and continuously refine deep learning and machine learning models, prioritising
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large