130 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"CNRS-" positions at King's College London
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intensive research and/or technologically focused environments, with a strong interest in science and technology, particularly in growing areas such as artificial intelligence. Strong networking
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to promote the industrialization of technology. ESSENTIAL QUALIFICATIONS/EXPERIENCES A Ph.D. (obtained or soon to be obtained) in Computer Science, Automation, Artificial Intelligence, Operations Research
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supports innovative research with state-of-the-art technology and offers exceptional opportunities to collaborate with leading scientists in molecular medicine and neuroscience. The Department is located in
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sensing, ecology, statistics, engineering, data science, quantitative social sciences, or a related discipline. Experience in developing models and mapping with real world data, with strong programming
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, participate in educational evaluation or research, and apply educational technology and automation tools to enhance resource management and delivery. Candidates with experience in these areas will have the
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procedures in a large organisation Highly numerate and experience in budget management and costings Highly proficient IT skills (including Excel, Word, Power BI) and experience of utilizing digital technology
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600 staff and students. The Department supports innovative research with state-of-the-art technology and offers exceptional opportunities to collaborate with leading scientists in molecular medicine and
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professional training programme, based in the Department of Psychology, School of Mental Health & Psychological Sciences (MHaPS), Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s College
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lecturer to develop and lead an ambitious programme of research in the field of PET Physics, with expertise and interest in PET technology, methodology and data analysis. This will involve collaborating with
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are looking for candidates to have the following skills and experience: Essential criteria PhD in spatial epidemiology, quantitative geography/remote sensing, ecology, statistics, engineering, quantitative