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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward
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search strategies and lexicons. Proficiency in fitting and validating statistical models or machine learning algorithms is essential, along with advanced skills in R and/or Python for data processing and
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PhD and have a few years of postdoctoral experience, preferably across multiple research-intensive environments other than QMUL for at least 3 years. Expertise in inflammatory diseases, particularly
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applicant will be expected to undertake a PhD as part of this post. There will be excellent opportunities for publication, and outputs crucial to public health decisions. The postholder will work directly
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research is expected to lead to training to computed tomography and computational modelling and the award of an MD or PhD at Queen Mary University of London and support the development of a future career in
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About the Role These are two Clinic Research Fellow posts in Haemato-Oncology. The successful applicants will be expected to undertake a research project resulting in a PhD in the Centre for Haemato
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collection across the region. For applicants without a doctoral degree, opportunities to undertake a PhD within the project will be offered. The position is full-time and fixed-term until 31 December 2028
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opportunities. The successful applicant will have a PhD in Experimental Solid-State Physics or a closely related area, as well as prior experience in a relevant field such as superconducting quantum devices
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in partnership to achieve excellence in research, education and translation of knowledge into policy and practice. We’re seeking an enthusiastic mathematical modeller interested in learning new skills