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lead the design, statistical optimisation and validation of assays for clinically relevant bladder cancer targets. Their central objective will be to develop an algorithmic workflow to detect new target
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rapid, targeted gene evolution while preserving host viability, enabling us to study fundamental evolutionary processes and develop new molecular solutions for problems in the areas of health and
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-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel algorithms for: Fine-grained video understanding Concept learning Temporal
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algorithms for automated driving. You could also develop your own research portfolio by supervising MSc individual research projects aligned with the Centre’s research themes. You will be expected
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collaboration that uses AI algorithms to recommend and coordinate experiments across distributed laboratories. Your work will focus on the synthesis and characterisation of AI-recommended conjugated materials
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developing/adapting computational models or algorithms to analyse biological data, and experience with single cell or spatial omics datasets or knowledge of cancer biology would be an advantage. What we offer
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aligned with the aims of the Terascale project. Develop and apply suitable methodologies for research for AI for science and catalyst discovery. Design, implement, and evaluate novel models, algorithms
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technologies across a wide range of electrical machine topologies and applications. This includes research into permanent magnet and non-permanent magnet machine drives, high- performance control algorithms
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successful candidate will contribute to the EU projects (with funding support from Innovate UK and UKRI), which aim to develop wireless communication optimisation algorithms for digital healthcare applications
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and