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Nuffield Division of Clinical Laboratory Sciences
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value: _________________________________________________________________________ Nuffield Division of Clinical Laboratory Sciences Job Description and Selection Criteria Job title Postdoctoral Research Assistant in Computational Pathology Division Nuffield Division of Clinical Laboratory Sciences Department Radcliffe Department of Medicine Location John Radcliffe Hospital, Oxford, OX3 9DU Grade and salary Grade 7: £36,2024 - £44,263 p.a. Hours Full time 37.5 hours Contract type Fixed-term 36 months Reporting to Prof. Daniel Royston & Prof. Jens Rittscher Vacancy reference 169386 Additional Information Two positions are available for this post. Research topic Artificial Intelligence-Based Assessment of Bone Marrow Biopsies: Improving the Assessment of Blood Cancer Using Multi-Centre Digital Pathology Datasets Principal Investigator / supervisor Prof. Daniel Royston Prof. Jens Rittscher (co-supervisor) Dr Hosuk Ryou (University of Oxford) Project team Dr Ros Cooper (University of Oxford) Emily Thomas (University of Oxford) Funding partner The funds supporting this research project are provided by Blood Cancer UK and Cancer Research UK _________________________________________________________________________ Nuffield Division of Clinical Laboratory Sciences https://doi.org/10.1038/s41375-022-01773-0 Recent publications https://doi.org/10.1182/bloodadvances.2020002230 The role Reporting to Prof. Daniel Royston (Principal Investigator) and Prof. Jens Rittscher (Co-investigator). The post holder will be a member of a research group with responsibility for carrying out research as part of a Blood Cancer UK project award. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants, technicians, and PhD and project students. Responsibilities • • • Implementation of image analysis solutions - Responsible for implementing adequate software solutions that address the identified clinical needs and process the correspo…

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comment: Applicants are invited for two PDRA position's at the Nuffield Division of Clinical Laboratory Sciences (Radcliffe Department of Medicine) - University of Oxford to participate in research relating to the improvement of diagnosis of blood cancer using computational pathology and machine learning. You will join a group of researchers in the fields of pathology and machine learning / computer vision techniques who are collaborating as part of BCUK & CRUK funded project awards. The quantitative analysis of histology image data has an increasingly important role in clinical research and offers the promise of augmenting and improving routine clinical diagnostics in blood cancer. The position is ideally suited for a postdoctoral researcher who has a strong background in biomedical image analysis, machine learning and computational biology. An academic / clinical pathologist and engineer will jointly supervise this post. You will be adapting and developing algorithms that make use of the latest machine learning and computer vision techniques to analyse cell and tissue morphology at different scales. The main area of research is the assessment of bone marrow trephines (BMT) in blood cancer, enabling objective and accurate assessment of disease subtypes with the identification of clinically relevant features. It will be necessary to develop a framework for processing large study cohorts and their statistical interpretation (with help from statisticians as needed). The position will be based in the Nuffield Division of Clinical Laboratory Sciences (NDCLS), Oxford. You will be working with pathologists looking to develop and evaluation next-generation technologies for use in clinical diagnostics. The post holder will spend their time between NDCLS and the BioMedIA Lab at the Institute of Biomedical Engineering (IBME) & Big Data Institute (BDI). You will have the opportunity to develop exciting new technologies and contribute towards their translation into the clinical environm…
application closing date: 2023-12-08T12:00:00+00:00
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