Research Fellow in Machine Learning

European Commission; United Kingdom; On-site; GBP 53,000 - 63,000; Full time

Job summary

A leading company in the UK is seeking a Research Fellow in Machine Learning to develop innovative methods for cancer research. The role involves designing advanced algorithms, collaborating with a multidisciplinary team, and publishing research findings. The ideal candidate will have a PhD and strong experience in machine learning, computer vision, and Python. This position offers a fixed-term contract and the opportunity to contribute to groundbreaking AI applications in healthcare.

Qualifications

• Experience developing novel machine learning methods for computational pathology.
• Strong experience with Python and deep learning frameworks.
• Ability to manage and supervise researchers for Grade 8.

Responsibilities

• Design and develop advanced machine learning methods for cancer research.
• Lead efforts in building multimodal deep learning models.
• Publish findings in high-impact journals and conferences.

Skills

Machine Learning

Computer Vision

Python

Deep Learning

Explainability in AI

Education

PhD in Machine Learning

PhD in Computer Science

PhD in Physics

PhD in Statistics

PhD in Mathematics

Tools

PyTorch

TensorFlow

Docker

Kubernetes

AWS

Job description

Organisation/Company KINGS COLLEGE LONDON Research Field Computer science Mathematics Physics Researcher Profile First Stage Researcher (R1) Country United Kingdom Application Deadline 1 Jun 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

About Us

PharosAI offers a unique cancer AI product development ecosystem for drug discovery and clinical applications, democratising access to data, AI models, technologies, and capabilities. PharosAI unites large-scale multimodal cancer datasets with AI models through a highly-secure, trusted, federated platform, offering state-of-the-art AI tooling for use by pharma/biotech/life-sciences, AI-pharma, and AI developers of clinical applications, in enterprises, growth companies, and research organisations.

PharosAI will revolutionise AI-powered cancer care, driving breakthrough therapies, clinical applications, addressing cancer’s social determinants, lowering barriers to UK SMEs, catalysing innovation and positioning the UK as a global leader in the dynamic healthcare and AI ecosystem.

About the role

Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision and imaging for cancer research, with an emphasis on computational pathology to identify biomarkers predictive of treatment response, prognosis, and disease progression. The successful candidate will also support and contribute to cutting-edge research focused on developing machine learning methods to integrate pathology with other complex data types - such as genomics, spatial biology, radiology, and electronic health records (EHRs) – as well as creating novel, transparent, and explainable AI approaches. At grade 8 the candidate will also supervise other researchers.

In this role, you will design and develop advanced machine learning methods - particularly in computer vision - for cancer and computational pathology research. Your work will span self-supervised and supervised learning, the development and fine-tuning of vision foundation models, multiple instance learning, survival analysis, and interpretable model development. You will also lead efforts in building multimodal deep learning models with a key focus on integrating pathology, radiology, and electronic health records (EHRs), while collaborating with the bioinformatics team to incorporate molecular data such as bulk RNA-Seq, whole genome sequencing (WGS), and spatial transcriptomics. A strong emphasis will be placed on explainability and transparency in AI, including techniques like saliency mapping, concept-based learning, and uncertainty quantification via conformal prediction. You’ll contribute to open-source projects, extending tools like MONAI for the computational pathology community, and support the data science team in training and fine-tuning large language models (LLMs) to extract structured clinical concepts from unstructured EHR, pathology, and radiology reports. The role involves publishing in high-impact, peer-reviewed journals and conferences, presenting findings to both academic and professional audiences, and collaborating closely with a multidisciplinary team of engineers, data scientists, clinicians, and biobankers. For Grade 8, the candidate will have managerial responsibility to supervise researchers (e.g. post-docs, PhD students) and lead research projects/programs.

This is a full time and you will be offered a fixed term contract until 31 March 2027.

About You

To be successful in this role, we are looking for candidates to have the following skills and experience:

• PhD in machine learning, computer science, physics, statistics, mathematics or related field.
• Demonstrated experience designing and developing novel machine learning and/or computer vision methods for either computational pathology, radiology, single cell or spatial transcriptomics and/or proteomics.
• Experience developing novel explainability and transparency in AI (XAI) methods for clinical and biological interpretability.
• Strong experience with Python and at least one deep learning framework such as PyTorch, PyTorch Lightning, TensorFlow or JAX. Familiarity with packages and technologies such as NumPy, Pandas, Scikit-learn, Scikit-image, OpenCV, Git, and Bash.
• Experience in developing and finetuning foundation models for biological applications.
• Experience working with HPC clusters (e.g. SLURM) or with cloud technologies such as AWS, Azure, or GCP.
• Evidence of high-impact, peer-reviewed publications and experience of presenting at academic/scientific/commercial conferences.
• For Grade 8: ability to manage and supervise researchers (e.g. post-docs, PhD students) and lead research programs.
• Experience developing multimodal ML (e.g. early/mid/late fusion) approaches for healthcare and/or biology e.g. computational pathology, genomics, transcriptomics and medical imaging.
• Experience with containerisation and orchestration tools such as Docker, Singularity and Kubernetes.
• Exposure to MLOps frameworks (e.g., MLflow, Kubeflow, Metaflow).
• Experience training or fine-tuning large language models (LLMs) such as LLaMA, GPT, or similar architectures on clinical or biomedical text, with a focus on concept extraction and information retrieval.
• Development and contributions to open-source research tooling and familiarity with frameworks such as MONAI.

Downloading a copy of our Job Description

Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process.

Further Information

We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community. We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.

We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

To find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages. Interviews: TBC We are not able to offer sponsorship for candidates who do not currently possess the right to work in the UK.

Grade and Salary:£53,149 - £62,422 per annum inclusive of London Weighting Allowance

Job ID:115225

Close Date:01-Jun-2025

Contact Person:Dr Gregory Verghese

Contact Details:[e-mail]