655 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Kingdom
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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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The Department of Electrical Engineering and Electronics is offering an exciting opportunity to work with Sony Computer Entertainment Europe Ltd (UK) to develop next generation gaming environments
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capable of driving the project forward. The ideal candidate: The ideal candidate will possess (or soon complete) a PhD in Theoretical Physics, Bio-Mathematics or Computational Biology. They will possess a
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skills, proficiency in quantitative analysis of large datasets and working with pre-trained machine learning models is desirable but not essential To apply online for this vacancy and to view further
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them in a future trial. Patient and public involvement in the development, interpretation and dissemination of findings will also be key. About you Applicants will possess a relevant PhD (or nearing
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Veronika Fikfak. The Postdoctoral Research Associate will be responsible for data collection from different human rights case law databases, coding (including machine learning) and data analysis. They will
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projects and publications from the group can be found here: https://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning
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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
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About us A post-doctoral research associate position is available at the Photonics & Nanotechnology group, Physics Department, King’s College London, funded by the EPSRC Programme Grant New