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at the Institute of Genetics and Cancer. Informal enquiries may be directed to Dr Athina Spiliopoulou (A.Spiliopoulou@ed.ac.uk ). Your skills and attributes for success: PhD in machine learning, genetic epidemiology
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(CBmE) was established in September 2006 in the Yong Loo Lin School of Medicine through a generous gift by the Chen Su Lan Trust. CBmE, directed by Prof Julian Savulescu, is a thriving centre for learning
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the High Performance Computing and Data Center, to be completed on campus by August 2026. This position collaborates with others in the growing machine learning and exoplanet subgroups within the Physics and
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. Perform any other duties relevant to the research programme. Job Requirements: PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive
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Engineering, etc.), expertise in cutting-edge AI and machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role
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by using explainable AI To develop generative AI techniques to design novel biologics for cancer Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or
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challenges from low carbon shipping and sustainable fuels to solar power technologies and advanced brain models. Learn more at https://mecheng.ucl.ac.uk . Within this dynamic environment, the Moazen Lab is
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processing and machine learning, as well as, online control of assistive systems. The PhD position is located in Aalborg, and the candidate will be a member of Neurorehabilitation Systems group at the Health
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, Safety and Health Regulations. • Assist in project resource requirements and managing student projects. Job Requirements: • Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering
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collaborative, impact-focused problem solver who wants to be part of a dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https