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chemical risk assessment through fundamental and applied innovative research, teaching and training in mechanistic and predictive toxicology. We are looking for an enthusiastic and creative PhD student to
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desirable): Autonomous laboratories for chemistry, materials, biology, etc. AI/ML for predictive modeling and inverse design Generative models, reinforcement learning, and agent-based approaches to
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Disorder Cocaine use disorder (CUD) remains a major public health challenge with no approved pharmacological treatments or predictive biomarkers. Emerging evidence suggests that the gut microbiome plays a
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. Compared to molecular systems, CLCs are slow, tunable, and accessible to imaging and single-particle tracking, enabling direct observation of their dynamics. They thus serve both as versatile model systems
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fidelity. Particular emphasis will be placed on integrating data-driven modelling with physics-informed deep learning to improve computational efficiency while maintaining physical realism and predictive
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model predictive control, machine learning, or reinforcement learning. Experience with IoT, edge computing, and cloud integration. Proven ability to contribute to research funding proposals
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College London in this area, go to: https://www.imperial.ac.uk/mechanical-engineering/research/ How to Apply For further details of the post contact Prof. Marc Masen, [email protected] Interested
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through model development, validation, deployment, publication, and technology transition. Research may address multimodal defect detection and classification, computational imaging and reconstruction
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through model development, validation, deployment, publication, and technology transition. Research may address multimodal defect detection and classification, computational imaging and reconstruction
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English. Experience with some of the areas of electrolyzer technologies, digital twins, model order reduction, system identification, power electronics, model predictive control, multi-objective