37 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of London
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-purposing. This role is a fantastic opportunity for someone passionate about leading innovative research and making impactful contributions to the field of computational biology. You will hold a PhD (or close
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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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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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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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the problem of induction”. How biological and artificial agents can use limited evidence to effectively learn and generalise is a long standing issue for psychology, AI/computational sciences, neuroscience and
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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practice impact while also learning about machine learning techniques. The successful applicant will work in the newly formed Health Equity Evidence Centre and innovative new centre that will generate data
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About the Role We are looking for a Postdoctoral Research Assistant to work with Dr Chema Martin on a Human Frontiers Science Program Research Grant project entitled “Evolutionary Biophysics
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and Immigration website . Full-Time, Fixed-Term (36 months) We are looking for a highly motivated early career researcher with a PhD (or near completion) in psychology, life sciences, genetics
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, contributing to our development and the success of our mission. The core responsibility of this role is the development of multiscale computational models, with particular emphasis on bio-based composite