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available, tailored to the needs and aspirations of the successful applicant. More information on the academic supervisor and EDC collaborations with JLR is available here: https://www-edc.eng.cam.ac.uk
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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Grand Tours, one-day races (monuments and semi-classics), and select World Tour 1-week stage races. The data sources will include video and previous race commentary to ‘code’ key events in races that help
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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ADTKD diagnostics and clinical trials. What you’ll do You will work at the interface of laboratory and data science, and clinical genetics. You will: Establish and characterise the UK ADTKD-MUC1 cohort
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biology, chemistry, psychology and social science, facilitating knowledge discovery. The intuitively uninterpretable high-dimensional data and network data become visually scrutable upon being mapped into 2
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the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. Please contact Mohammad Reza Ilkhani ezzmi1@exmail.nottingham.ac.uk for further information and an
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and an Industrial supervisor at Jaguar Land Rover (JLR). It falls within the remit of the Cambridge Engineering Design Centre (EDC), but interactions with other groups are expected, across and beyond
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, or physics, and will demonstrate a willingness for experimental fieldwork and data analysis. This PhD offers a unique opportunity to contribute to frontier research in atmospheric chemistry, with
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access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has outstanding facilities and works in