40 big-data-and-machine-learning-phd Postdoctoral research jobs at University of London
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robotics, mechanical engineering or a similar engineering field. The job requires an in-depth knowledge about soft inflatable/eversion robotics, sensor data acquisition and processing, computer and system
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to using data to revolutionise our understanding of cancer risk and enable early interception of cancers (Queen Mary media & Cancer Research UK News ). You will use large primary care and other diverse
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. The post-holder will participate in lab meetings, journal clubs, departmental research meetings, and co-supervise students. They will also present data at high-profile international and national meetings
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at scale. About You Applicants should preferably have an MSc/PhD in Computer Science/Engineering. They should have expertise in distributed systems and computer networks. Excellent knowledge and practical
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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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of Engineering and Materials Science, a large School with 108 academics, more than 250 PhD students and over 2500 undergraduate students. It is one of five schools in the Faculty of Science and Engineering at
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to completion*) in a relevant subject and a proven track record in computational biology and data science, coming from either a bioinformatic or computational background. With experience of working with large
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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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. Research will focus on identifying and publishing results in methods to build foundation models, using multimodal and multiscale health data. The role is funded for 24 months in the first instance. About You
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve