63 computer-programmer-"https:"-"CNR" "https:" "https:" "https:" "https:" "https:" "Dr" "P" uni jobs at Imperial College London
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help create the next generation of doctors and scientists—benefiting patients and populations globally. We are seeking a highly motivated individual to join our team as Programme Administrator
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of universities, informing research strategy, and determining the allocation of significant public research funding. Preparing a successful REF 2029 submission is therefore a complex institutional programme that
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seeking to maximise Imperial's potential as a force for good in the world. Our Imperial Class of 2030 programme will nurture the most talented, enterprising and diverse graduating class we have ever served
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offer you an exciting opportunity to developan independent research programme building on existing strengths in one of the departments within the Faculty of Medicine. You will contribute to a research
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.'’ What you would be doing: The successful candidate will work closely with Dr Steven Sivek on some aspects of the EPSRC grant titled "Floer homology and monodromy." This position is well-suited
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teams, from assay design and microbiology (Dr Andrew Edwards) to data science (Dr Marko Storch) and AI/ML (Prof. Alessandra Russo, Prof. Ramon Villar, Prof. Mauricio Barahona). In addition to your
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multidisciplinary teams, from assay design and microbiology (Dr Andrew Edwards) to data science (Dr Marko Storch) and AI/ML (Prof. Alessandra Russo, Prof. Ramon Villar, Prof. Mauricio Barahona). In addition to your
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and our excellent professional development opportunities, here: http://www.imperial.ac.uk/jobs/benefits/ We have an opening for a position as a Postdoctoral Research Associate in the Department
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of Imperial’s academic community. Our professional team has supported academics to deliver large, high-profile, national and international programmes to over 500+ clients, in more than 40 countries. You can
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. Stefanos Zafeiriou can be found at https://wp.doc.ic.ac.uk/szafeiri/ . Research Associate: A PhD (or be close to completion) in an area pertinent to the subject area, i.e. computer vision, machine learning