Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Postdoctoral Transition Fellow (Senior Research Associate)

University of Cambridge
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Faculty Fellowship Programme Data Science (January 2026)

Faculty Fellowship Programme Data Science (January 2026)

Faculty Fellowship Programme Data Science (January 2026)

Postdoctoral Data Scientist Engineer for the Quantitative Neuroradiology Initiative

Research Fellow in Data Science and Analytical Chemistry

Research Fellow in machine learning and spatial statistics

We are seeking to recruit a highly motivated Postdoctoral Transition Fellow in Machine Learning and Cancer to join Professor Richard Gilbertson's group at the Cancer Research UK Cambridge Institute as part of the Cancer Research UK Children's Brain Tumour Centre (CRUK CBTCE).

The CRUK CBTCE launched in 2018 and is hosted by the University of Cambridge and The Institute of Cancer Research, London. Brain tumours remain the most common cause of cancer-related death in children. Limited progress in these diseases relates directly to the use of inaccurate preclinical pipelines that fail to identify drugs with activity in patients. The CRUK CBTCE convenes a critical mass of expert personnel, infrastructure and global collaborations in paediatric brain tumour biology, medicinal chemistry, pharmacology, together with expertise in preclinical and clinical trials. Our research strategy is centred around our innovative pipeline that aims to generate curative treatments for children with brain tumours. The CRUK CBTCE has received an additional 5 years of funding from CRUK and is currently expanding capacity, building on the success of our previous 6 years programme.

We are recruiting a Postdoctoral Transition Fellow to develop an independent research project using artificial intelligence and machine learning to create the world's first entirely digital models of the hardest to treat children's brain tumours. The models will be used to help identify new treatment targets, develop potential new drugs and test them via virtual clinical trials within computer models of cancer. The role will focus on the development of state-of-the-art machine learning approaches for the analysis of spatial sequencing data of childhood cancers including medulloblastoma and ependymoma in collaboration with the Alan Turing Institute, London and MD Anderson Cancer Center, Texas USA.

Fixed-term: The funds for this post are available for 2 years in the first instance.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check and a security check.

We are anticipating a multiple round interview process with the first round to be held early December 2024 and in person interviews to be held in January 2025.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.