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Postdoctoral Researcher in Machine Learning and Cancer

University of Oxford - Nuffield Department of Women’s & Reproductive Health, Big Data Institute

Location: Oxford
Salary: £36,024 to £44,263 per annum, Grade 7
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 15th July 2024
Closes: 5th August 2024
Job Ref: 173663

Location: Nuffield Department of Women’s & Reproductive Health, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Old Road Campus, OX3 7LF

Grade 7: £36,024 to £44,263 (with a discretionary range to £48,350) per annum

The Nuffield Department of Women's & Reproductive Health is seeking a Postdoctoral Researcher in Machine Learning and Cancer to join Professor Christopher Yau's group at the Big Data Institute at the University of Oxford. 

The position is embedded within a research programme funded as part of a UKRI Turing AI Fellowship. The role will focus on the development of state-of-the-art machine learning approaches for the analysis of spatial sequencing data of cancers in collaboration with the Jamieson Group at the University of Glasgow. This is a unique opportunity to develop and apply AI to tackle key questions in cancer research, and is an ideal opportunity for a soon-to-complete or recent doctoral graduate seeking to switch disciplines into machine learning. An interest in biology or medicine is essential. The postholder should also be self-motivated, diligent and able to work individually or collaboratively. 

The successful candidate will have a PhD in a quantitative subject (e.g. mathematics, physics, computer science, engineering) and possess experience of developing computational models.

Please note:  this post is fixed-term for 12 months but must end by 31st December 2025. The post is available from 1st October 2024.

Applications for flexible working arrangements are welcomed and will be considered in line with business needs.

You will be required to upload a CV and Supporting Statement as part of your online application. Click here for information and advice on writing an effective Supporting Statement.

The closing date for applications is 12.00 noon on Monday 5th August 2024. Interviews will be held in mid-August.

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