Data Scientist in the Coronary Research Group

Corehr
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist, Quantitative Biosciences ...

Data Scientist (Mid-level) ...

Data Scientist

High Salary! Data Scientist – PhD Computer Science,Recommender Systems, NLP, Machine Learning, Java ...

Data Scientist

Genomic Data Scientist (we have office locations in Cambridge, Leeds & London)

Data Scientist in the Coronary Research Group

Department: SCMMS Southbank

About Us

The School of Cardiovascular and Metabolic Medicine & Sciences (Head, Professor Mauro Giacca) provides an outstanding multi-disciplinary environment for the pursuit of cutting-edge cardiovascular and metabolic research. Our current research spans the fundamental molecular, cellular, and physiological processes that underlie normal and abnormal cardiovascular and metabolic function and drive the translation of this strong basic science into advances in clinical practice. The School occupies facilities across the Guy’s, St Thomas’ and Denmark Hill campuses of King’s College London and comprises over 70 clinical and non-clinical academic groups, hosting 400 personnel and 110 PhD students. Clinical and pre-clinical researchers at King’s have access to state-of-the-art core facilities and expertise, including multimodality in vivo imaging, clinical research facilities, experimental medicine hub, high-throughput robotic screening, comprehensive genomics/proteomics/metabolomics/single cell analyses, integrative invasive and non-invasive human physiology, and comprehensive murine physiology and genetic modification. There is an innovative clinical informatics platform integrated with large language models for the analyses of electronic health records across the King’s Health Partner NHS Trusts. Assisted by the close collaboration between clinical and academic colleagues and the outstanding infrastructure, all the building blocks are in place for the generation of novel advances with major clinical impact. The School hosts a range of training programmes including three PhD programmes in cardiovascular sciences and advanced therapies, an MSc in Cardiovascular Sciences and an iBSc in Cardiovascular Medicine. Multiple other doctoral training programmes are available across the Faculty.

About the Role

The postholder will contribute to the development of our portfolio of clinical and health informatics platforms and research which sits within the King’s BHF Centre of Research Excellence (https://www.kcl.ac.uk/scms/bhf-centre) and specifically work within the Coronary Research Group at KCL.

The Coronary Research Group carries out translational research into the mechanisms and consequences of cardiac ischaemia with a view to developing and evaluating novel and personalised treatments for ischaemic heart disease. The group employs diverse research methodologies to achieve these aims, from exploration of the pathophysiological basis of disease states by detailed characterisation of patients during diagnostic and therapeutic procedures through designing and conducting multicentre randomised clinical trials to applying machine learning and Artificial Intelligence techniques to data extracted from routine health records. The work will also include areas relevant to the BHF Centre Themes including heart failure, obesity, and metabolic diseases with the scope of extending the timeframe of the contract based on the receipt of renewed funding. The Group’s research is funded by peer-reviewed grants from charities (including the Academy of Medical Sciences, British Heart Foundation, and Medical Research Council) and public funding (UK National Institute for Health Research and US National Institute for Health) as well as investigator-initiated commercial funding.

The role will build clinical NLP and phenotyping using electronic health records, putting these tools in the hands of clinical users. As such, this tool is a foundational piece of work to enable a multitude of subsequent projects and grant applications which use this software to identify a cohort of patients from the EHR.

This is a 50% FTE post (17.5 hours per week), and you will be offered a fixed term contract for 8 months.

About You

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

  • PhD or equivalent experience in a relevant area
  • Knowledge or interest in Natural language processing ideally over big biomedical data
  • Software development experiences in large-scale academic projects and/or industry environment
  • Data management in large scale and heterogeneous data spaces
  • Clinical Informatics
  • Biomedical ontologies / Semantic Web technologies
  • Information retrieval, data analytics and/or text mining on Electronic Health Records and biomedical literature
  • Knowledge of machine learning / deep learning with an interest in the application to electronic patient records
  • Understanding or interest in graph data models / Knowledge graph techniques
  • Some statistical skills

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.

Interviews are due to be held in April-May.

Grade and Salary: £44,355 - £49,128 pro rata per annum, including London Weighting Allowance. Job ID: 113107

Post Date: 14-Apr-2025 Close Date: 28-Apr-2025

Contact Person: Haseeb Rahman Contact Details:

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!