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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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personalised, ethnically-stratified risk scores. This is a highly interdisciplinary project at the intersection of machine learning, health equity, and precision medicine. The successful candidate will join a
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control strategies integrating fuel, engine, electric machine, and energy recovery systems for improved overall efficiency. Validate the developed methods through experimental and simulation studies
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for the prevention of IAI. The person taking on the project will need to work closely with the clinical teams and the patients and to do laboratory and computer-based work. A clinical qualification is not a
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. 3. How to Apply Those interested should send a CV and personal statement to Dr Nasim Mahmoodi (n.mahmoodi@bham.ac.uk) via the above 'Apply' button. Funding notes: Funding is available on a competitive
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How does experience shape the brain? We aim to understand why distinct experiences result in adaptation through learning, whilst others can lead to unsurmountable stress, psychiatric and behavioural
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, cooperative operation among connected electrified vehicles such as airport trailers, delivery pods, or urban mobility fleets. Using multi-agent systems, reinforcement learning, and digital-twin technologies
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are most useful. Tropical, extra-tropical and post-tropical cyclones will be considered. To increase the usefulness of respective seasonal forecasts the project will focus also on the understanding
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How does experience shape the brain? We aim to understand why distinct experiences result in adaptation through learning, whilst others can lead to unsurmountable stress, psychiatric and behavioural
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to obtain) at least a 2:1 undergraduate degree, and a MSc/MEng is desirable. 3. How to Apply Those interested should send a CV and personal statement to Dr Nasim Mahmoodi (n.mahmoodi@bham.ac.uk) via the above