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“hidden” (latent) state representation of the game and a way to map that state to a value—essentially, how good the situation is for the AI at any given point. Once we have this, the AI can sample a range
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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. Like other glycans, they are not built against a defined template, and yet their structure is non-random, with specific motifs within the glycan chains defining binding sites for critical signalling and
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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on electromagnetic motors, pumps, or compressed air systems. However, motors are often bulky, heavy, and rigid, while fluid systems are typically tethered and inefficient. There is an urgent need for untethered soft
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of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject (physics
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of quantum computing and an understanding of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s
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4-Year PhD Studentship: Deciphering how domain organisation regulates heparan sulphate function Supervisors: Prof Cathy Merry, Prof. Kenton Arkill, Dr Andrew Hook Overview Glycosaminoglycans (GAGs
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THIS VACANCY IS OPEN TO INTERNAL APPLICANTS ONLY About us: We look forward to welcoming the successful candidate to the ESRC Centre for Society and Mental Health (CSMH; www.kcl.ac.uk/csmh ) and the
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as structural members when deployed make a good basis for a deployable structure. The two main aims of this project are to develop novel designs and manufacturing methods for foldable composite