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with IoT, edge computing, and cloud integration in rural or resource-constrained settings. Proficiency in MATLAB/Simulink and AI/ML tools like TensorFlow or PyTorch. Excellent programming skills (e.g
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applicant will be supported in conducting quantitative research (e.g. multinational surveys, online experiments, analysis of existing data sets, computational textual analysis, etc) in this area of research
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Applications are invited for a Postdoctoral Research Assistant in Data processing for the MIGHTEE survey. This is a senior role funded through the UKRI Frontier Research Grant of Prof. Matthew Jarvis to lead the processing of the MIGHTEE continuum and HI survey data. The role requires a high...
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About us We are looking for motivated researchers to apply for the postdoctoral research associate position in robotics and AI, funded by our new EPSRC project titled “Circular Robot 5.0: Industry Wide Data-Driven Circular Economy of Industrial Robots”. The candidates are expected to have...
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candidate should have (or expect to soon be awarded) a PhD in quantum information theory (including some aspects of quantum computing, quantum cryptography and/or quantum communication) and some experience in
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development laboratories at Guy’s Campus, London Bridge. The group specialises in inventing custom fluorescence-lifetime and multiphoton technologies and coupling them with powerful computational pipelines
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supporting the general program of research within the pre-clinical team. You will work in Containment level 2 and 3 facilities to assist with murine immunogenicity experiments, murine aerosol challenge
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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development
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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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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing