667 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in United Kingdom
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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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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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scientific discipline. Experience in developing and running an atmospheric transport model. Experience in interpreting data. Experience with FORTRAN and Python computer languages. Proven ability to work
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essential. Experience with MATLAB or Python computer programming for neuroimaging data analysis is essential. Experience in MRI and/or EEG acquisition and analysis is desirable. Experience working on research
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-term persistent infections, as well as on newly emerging variants of concern (VOCs). We are seeking a highly motivated candidate that has obtained (or will obtain soon) a PhD in a relevant subject (i.e
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completion) in AI, Machine Learning, Data Science, Control or Energy Systems Engineering, or a related field. Strong expertise in AI for real-time systems, predictive analytics, or Digital Twins. Experience
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apply if You have: A relevant PhD (completed or soon to be achieved) preferably in Experimental Psychology, Neuroscience or related fields (e.g. Computer Science, Data Science). Demonstrated experience
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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
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the university strategy tying together our mission, vision and values. You will: Manage and organise day‑to‑day research tasks identifying and resolving technical, logistical or practical challenges