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Job vacancy: ACRC Fellow

    The Advanced Care Research Centre (ACRC) and the School of Informatics are offering one proleptic fellowship for researchers with the potential to develop into leading research-active academics at the of Edinburgh. We are particularly interested in people who can develop an innovative and novel independent research programme focusing on health and social care technologies applied to care in later life, or multimorbidity or healthy ageing.

    Candidates are encouraged to speak ACRC leads before applying. Please direct any enquiries to ACRC Director Prof Bruce Guthrie Bruce.Guthrie@ed.ac.uk, or ACRC Informatics Lead Prof Jacques Fleuriot Jacques.Fleuriot@ed.ac.uk.

    Job and application details can be found here.

     

     

    Opportunity: Multimorbidity PhD Programme for Health Professionals

      The Clinical PhD Research Fellowships are fixed term 3-year appointments offering training, mentoring and support to health professionals undertaking a PhD on the topic of multimorbidity.

      We are looking for applicants who are interested in working on understanding the “Co-existing mental and physical multimorbidity, adverse events, and longer term outcomes in hospitalised patients with sepsis“.

      More info available here.

      Programme Co-ordinator post available on Artificial Intelligence for Multiple Long-Term Conditions Programme

        We are looking for an experienced researcher (Grade 8, salary £42,149-£50,296), with a PhD in Artificial Intelligence, machine learning or data science, to coordinate and support the delivery of our core AI research programme and well as overarching programme management. This a joint post between the School of Medicine and the School of Informatics at the University of Edinburgh.

        Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC) is a 3 year, £3.9 million research programme funded by the National Institute for Health Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions Programme. AIM-CISC is led by a multidisciplinary team from The University of Edinburgh, University College London and NHS Lothian. This includes clinical and genetic researchers studying complex multimorbidity, public partners, social scientists researching wider social and spatial determinants of health and care, and informatics and data science academics with AI expertise across multiple domains including natural language processing, machine-learning including multilayer network analysis, and applied AI.

         

        Three postdoctoral Research Associate posts available in Artificial Intelligence for Multiple Long-Term Conditions Programme

          Applications are invited for 3 Research Associates in Machine Learning for Health, Network Science, Knowledge Representation and AI to work within the Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC) programme in the School of Informatics and Usher Institute, University of Edinburgh.

          Artificial Intelligence and Multimorbidity: Clustering in Individuals, Space and Clinical Context (AIM-CISC) is a 3 year, £3.9 million research programme funded by the National Institute for Health Research (NIHR) Artificial Intelligence for Multiple Long-Term Conditions Programme. AIM-CISC is led by a multidisciplinary team from The University of Edinburgh, University College London and NHS Lothian. This includes clinical and genetic researchers studying complex multimorbidity, public partners, social scientists researching wider social and spatial determinants of health and care, and informatics and data science academics with AI expertise across multiple domains including natural language processing, machine-learning including multilayer network analysis, and applied AI. The research areas are broadly as follows:

          1.Network Science for the analysis and prediction of multimorbidity.

          2. Machine Learning for clustering of complex multimorbidity.

          3. Knowledge Representation for Medical Artificial Intelligence