25 image-processing-and-machine-learning Fellowship positions at University of London
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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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& International Health is seeking to appoint a Research Fellow in Health Data Science (with a focus on machine learning) to NeoShield , a multi-country implementation research programme focused on neonatal sepsis
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, low noise measurement in DC and microwave range. You will have computer programming skills, and experience of simulation packages. You will be a good communicator and the ability to work in a
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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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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
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. The post-holder will be responsible for bringing forward an innovative programme of work to investigate the impact of the OptiMAx programme through mixed-methods process evaluation and gender analysis
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will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process may be addressed to jobs@lshtm.ac.uk . Please quote reference ITD-CRD-2026-10
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queries regarding the application process may be addressed to jobs@lshtm.ac.uk . Please quote reference PHP-HSRP-2026-07. The supporting statement section should set out how your qualifications, experience
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the application process may be addressed to jobs@lshtm.ac.uk . Please quote reference PHP-PHES-2026-07. The supporting statement section should set out how your qualifications, experience and training meet each
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policies, flexible working arrangements, and campus facilities. Queen Mary’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made