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Queen Mary University of London invites applications for a Postdoctoral Research Assistant in Artificial Intelligence and Digital Pathology. The role focuses on developing AI-driven tools for biomedical imaging and pathology data, with responsibilities across independent and collaborative research, algorithm development, and dissemination.
The successful candidate will join a multidisciplinary team, contribute to translational research, and work in a leading academic environment with
General Description:
Queen Mary University of London is seeking to appoint a Postdoctoral Research Assistant to contribute to pioneering research at the intersection of artificial intelligence and digital pathology. The position is based within a leading academic research environment and supports ongoing projects focused on applying advanced computational methods to biomedical imaging and pathology data.
The successful candidate will work as part of a multidisciplinary team involving clinicians, data scientists, and researchers, contributing to the development and application of AI-driven tools for the analysis of complex medical datasets. The role includes designing and implementing machine learning models, processing large-scale pathology imaging data, and contributing to translational research aimed at improving diagnostic and clinical outcomes.
Responsibilities include conducting independent and collaborative research, developing novel algorithms and computational pipelines, preparing research outputs for publication in high-impact journals, and supporting grant-related activities. The postholder will also engage in academic dissemination through conferences and workshops and contribute to the broader research objectives of the institution.
This is a fixed-term research position offering an opportunity to work within a highly collaborative and internationally recognised research setting, with access to state-of-the-art facilities and resources.
Eligibility Criteria:
Required Expertise/Skills:
Salary Details:
£36,572 – £43,722 per annum (Grade 4)