Overview An experienced image analysis and computing scientist is required to work as part of the Sheffield Platform for Imaging Research in Oncology (SPIRO) at the University of Sheffield. SPIRO is a £4M+ transformative capital investment funded by Yorkshire Cancer Research, aiming to establish the University as a leading centre for oncological imaging research. The role is based at the University MRI Unit within the Section of Imaging, Division of Clinical Medicine and is mentored by Dr Bilal Tahir, Professor Jim Wild and other SPIRO investigators. The position sits within Work Package 4 (Technology Integration and Computational Analysis) and will work closely with the Insigneo Institute for in silico Medicine and the Centre for Machine Intelligence. Main Duties and Responsibilities

Develop and apply advanced image analysis techniques, including classical and AI-based methods, to extract meaningful insights from multi‑modal cancer imaging data (PET, MRI, Photon‑Counting CT). Create automatic and semi‑automatic segmentation tools to identify and classify regions of interest, including tumours, across different imaging modalities. Develop AI‑driven radiomics models and predictive analytics for cancer diagnosis, treatment planning and response assessment. Implement robust pipelines for image and data analysis on shared high‑performance computing infrastructure. Integrate functional, metabolic and structural imaging data across modalities for comprehensive assessment of cancer structure, metabolism and function. Contribute to the supervision of PhD and undergraduate students in the research group. Actively participate in national and international collaborations with academic, clinical and industrial research partners. Analyse and record data to aid future research and produce useful findings. Publish high‑impact papers as a co‑author. Present results to collaborators, research group members and external audiences to disseminate and publicise findings. Support the clinical translation of developed methods through collaboration with clinical partners. Carry out other duties commensurate with the grade and remit of the post.

Person Specification We value a diverse community where all staff feel respected and included. Candidates will be encouraged to apply even if their past experience does not match perfectly with the role's criteria. Essential Criteria

Good Honours degree in Physics, Engineering, Computer Science or related discipline (or equivalent). PhD in medical image processing/analysis (or equivalent). Experience with artificial intelligence (machine learning/deep learning). Experience with classical image processing techniques (e.g. classification/segmentation/registration). Experience with multi‑modal medical image analysis. Strong programming skills and experience with high‑performance computing environments. Track record of publication in computational and imaging journals as a primary author. Effective written and verbal communication skills, report writing skills and experience delivering presentations. Experience of working in a multi‑disciplinary team. Practical experience of working with oncological images.

Desirable Criteria

Ability to supervise PhD students and researchers in technical aspects of image computing and artificial intelligence.

Salary £38,784 - £47,389 per annum, with potential to progress to £51,753 per annum through sustained exceptional contribution. Work Arrangement Full‑time Duration Up to 31/08/2030 Line Manager Senior Lecturer in Cancer and Lung Imaging Benefits

Minimum of 41 days annual leave including bank holidays and closure days (pro‑rata) with the ability to purchase more. Flexible working opportunities, including hybrid working for some roles. Generous pension scheme. Range of discounts and rewards on shopping, eating out and travel. Staff networks providing opportunities for social interaction, peer support and personal development (Race Equality, LGBT+, Women’s and Parent’s networks). Recognition awards to reward staff who go above and beyond. A commitment to development access to learning and mentoring schemes; integrated with academic career pathways. A variety of generous family‑friendly policies:

Paid time off for parenting and caring emergencies. Support for those experiencing menopause. Paid time off and support for fertility treatment. And more.

Equal Opportunity We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process. #J-18808-Ljbffr