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successful in this position, you will ideally bring the following: For the Networking and AI position: Completed a PhD in Computer Science, Electrical & Computer Engineering, or a closely related field Expert
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(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as
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national (University of Manchester) and international (University of Regensburg, Forschungszentrum Jülich, Free University of Berlin) partners. Successful candidates will hold a PhD in spintronics, magnonics
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maximum of six hours per week. About you You will have a PhD (or near completion) in a relevant discipline (e.g. geography, GIS, data science, public health, or a related field) or equivalent research
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of the brain. The two labs have already successfully collaborated on several projects (including: PMID:35213723; PMID:39915814; PMID:40298030 and doi:10.1101/2024.08.14.607977), co-supervise three PhD students
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gas compositions. They will apply and develop models to account for the observed gas distribution in the context of East African Rift geological system. The postholder will also be responsible
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an interdisciplinary team working across physical and computer science to develop new pathways to the design and discovery of inorganic materials as part of the Leverhulme Centre for Functional Materials Design. This
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MRI (fMRI), functional Ultrasound Imaging (fUSi) and computational modelling of emotion-related behaviours. This is an exceptional opportunity to develop your research portfolio within a team of
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engagement in applied health care research and the literature on health inequalities. You should have a PhD degree in relevant areas of Public Health or relevant disciplines e.g. sociology, psychology
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the guidance of Professor Emmanuil Georgoulis. Relevant skills are a PhD (or near completion of a PhD) in Numerical Analysis, or Scientific Computing, or related field. The position requires good programming