25 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions at University of London
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Trust-funded project on Plasma-Assisted Combustion (PAC) Modelling of Ammonia, in collaboration with the York Plasma Institute. The successful candidate will develop and apply advanced computational
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School, we are known for our pioneering research and pride ourselves on our international reputation. We are equal first in the UK for the impact of our Computer Science research, and second for our
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behaviour observed in laboratory studies. You will work closely with Professor Kostas Stathis (Department of Computer Science, Co-Investigator) and Professor David Levine (Leverhulme Fellow and Principal
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas
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Computer Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic
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About the role This role supports a multidisciplinary programme investigating the role of the Maresins, a family of pro-resolving lipid mediators, in early cancer development. You will process
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an interdisciplinary team, engaging effectively with colleagues working across social science, law and data science. They will be organised, methodical, and able to communicate complex research insights clearly
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nearing completion) in Bioinformatics, Computational Biology, Genomics, or a related field, and proven experience in analysing high-throughput sequencing data. They will be proficient in R and/or Python and
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effectively with colleagues working across social science, law and data science. A strong understanding of migrants’ interactions with welfare systems, and of the social implications of welfare-AI is essential
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to a broader computational strategy for next‑generation polymer design. About You You will have, or be close to completing, a PhD in materials science, engineering, physics, chemistry, or a related area