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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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bone marrow transplantation. We are looking for a highly motivated candidate with a PhD degree interested in using microbiological methods with the aim of developing novel strategies to improve bone
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the system Development of inverse design frameworks using machine learning Development of full simulation for the chip-scale chirped-pulse amplification Use the full simulation to guide system fabrication
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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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. 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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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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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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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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. The main objective of the project is to study the interaction between machine learning and wireless communication fields. The successful candidate will answer questions such as how to assign limited