82 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"St" positions at King's College London
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to the design and evaluation of human–computer interface prototypes through design sprints and usability testing. This is a full-time, fixed-term post until December 2027, working at the interface of clinical
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises Chemistry, Engineering, Informatics, Mathematics, and Physics – all departments highly rated in research
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teams are fully trained through a structured upskilling programme and that services are delivered cost-effectively and represent value for money. You will promote energy efficiency and support the
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international partners and maintains strong links with rheumatology and primary care services throughout the NHS. We have an active programme of patient and public involvement, which informs all stages of our
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in health and disease and apply this knowledge to the development of new and innovative clinical practise, alongside providing a rigorous academic programme for students. About the role Applications
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written communication skills, with advanced computer use and strong interpersonal and influencing/behavioural skills to build a strong network to support the delivery of the service 5. Ability to work
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Programme Director), and Consultancy and Capacity building work with Abdullah-Al-Salem University in Kuwait. About the role To support these and future ventures, we are now seeking a senior clinical medical
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based in the Department of Informatics within the Faculty of Natural, Mathematical & Engineering Sciences (NMES), an internationally recognised centre for research in robotics, artificial intelligence
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studies Proficiency in cell culture and differentiation Experience with iPSCs Knowledge of PCR, RT-qPCR and other molecular biology techniques Proficient in computer use Understanding of the day-to-day
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clinical base at the Maudsley Hospital and involves affiliated laboratories across King’s Health Partners. The programme is strongly lead by statistical modelling to predict not just Parkinson’s disease (PD