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Field
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measurements and collaboration with related valve disease projects. • IDIBAPS, Spain (2 months): access to clinical datasets and validation of developed algorithms against clinical and in-silico data. About You
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opportunity for an experienced researcher to lead the development of decentralised swarm control algorithms for underground pipe operations. You will join an international research programme funded by
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concurrent algorithms can themselves be vulnerable. In particular, well-understood safety conditions such as linearisability do not guarantee security, and current approaches to addressing this issue lead to
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processing, and software-defined radio experimentation. Depending on your background and interests, your research may emphasize theoretical modelling and algorithms, experimental implementation, or a
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algorithms, validated in real-time simulations and experimentally in collaboration with industry. The project: This project looks at the development of electromechanical friction wheel braking (EMB) systems
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algorithms. Vision Language Model (VLM) experience is desirable. Qualifications A high-grade undergraduate degree (first class or upper second) in computer science or MSc in related field. Skills Knowledge
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high-frequency ultrasound imaging platform, including hardware-software integration and advanced signal processing algorithms for structural and functional imaging, in order to deliver clinically
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have submitted your thesis and be awaiting viva. Essential criteria include experience of conducting and publishing high-quality AI research, strong knowledge of AI algorithms, programming experience in
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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learning algorithms. Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes