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help supervise associated PhD students. The successful candidates will join large, supportive research teams led by Profs Knight, Screen and Connelly all working collaboratively at Queen Mary. This is an
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research teams led by Prof Knight, and Prof Screen working collaboratively at Queen Mary. The PDRA will interact with a team of academics, PDRAs, and PhD students, working on related organ-chip models, as
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, conducting simulation studies, analysis of datasets from economic and social research studies, software implementation and delivery of workshops. The Research Fellow will be supervised by Prof. Jonathan
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discipline such as Emergency and Critical Care, Cardiology or Anaesthesia and Analgesia. A background in research in cardiopulmonary medicine or surgery and a PhD, although desirable, are not essential. We
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background in research in cardiopulmonary medicine or surgery and a PhD, although desirable, are not essential. We offer a generous reward package and benefits including: Competitive and attractive pension
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to their own research interests. About You Candidates should have a PhD in a relevant discipline or will have obtained it by commencement of the position. Candidates should have some experience in multi
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sequencing data from individuals with the C9orf72 repeat expansion. This post requires extensive experience in analysis of genomic data, supported by a PhD. They will support the development and applications
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architectural choices for neural networks. This project will be in collaboration with Prof. Mark Sandler from the Centre for Digital Music – a world-leading research centre in the field of AI for Music and Audio
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to cancer treatment delays. The successful candidate will join 50 researchers on 10 National Cancer Audits https://www.natcan.org.uk/ . The postholder will report to Prof Ajay Aggarwal (co-PI, TACTIC and
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, while engaging with researchers from different disciplinary and country backgrounds. For more information please contact: Prof. Dina Balabanova, dina.balabanova@lshtm.ac.uk . The post is part-time 17.5