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Are you a researcher driven to understand and predict the fundamental mechanisms limiting lithium-ion battery performance? We are recruiting a Research Associate in Lithium-Ion Battery Modelling
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, and generate high-quality datasets for predictive microbial modelling and risk assessment. Responsibilities include contributing to the design and execution of food challenge studies, integrating
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, manufacturing) by creating applications for critical systems, adaptive and autonomous systems, advanced perception, diagnostics, quality control, and prediction systems. Further research areas include precision
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contents in a robust, interpretable, and industrially deployable manner. The PhD project will develop a unified framework combining multi-degree-of-freedom dynamic modeling, high-bandwidth nonlinear
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Application deadline: All year round Research theme: Environmental geochemistry How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD studentship is open to EU, UK, and US applicants. The
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of existing studies to promote the use of risk-informed decision frameworks, prediction models, AI applied to planetary protection. Tasks include: Support the creation of probabilistic models for planetary
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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learning, generalization/robustness and privacy aspects in scalable learning algorithms. Large‑scale optimization and control: Optimal control, model predictive control and other optimization‑based control
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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model predictions with biological knowledge and external data sources. Work closely with academic partner groups and the Innovation & Business (I&B) team to align technical development with biological