Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a pioneering team to develop AI solutions for cancer care and improve patient outcomes.
- Company: Be part of Queen Mary University’s innovative PharosAI initiative, transforming cancer treatment in the UK.
- Benefits: Enjoy flexible working arrangements, comprehensive staff benefits, and a supportive, inclusive environment.
- Why this job: Make a real impact in cancer research while collaborating with top scientists and clinicians.
- Qualifications: PhD and medical degree required, with experience in histopathology and machine learning techniques.
- Other info: This role is part of a larger project with multiple exciting opportunities across various disciplines.
The predicted salary is between 36000 - 60000 £ per year.
About the Role
About the Project
We are seeking a talented and dedicated team of scientists, bioinformaticians and support colleaguesto join the ground-breaking PharosAI initiative – a £43.6M national programme co-led by Queen Mary University of London. PharosAI is set to revolutionise AI-powered cancer care, accelerating the development of breakthrough therapies, advancing clinical applications, and improving access to cutting-edge technology across the UK healthcare and biotech sectors. Read more about the initiative here
This is a unique opportunity to help build a first-of-its-kind cancer AI development ecosystem, democratising access to data, technologies, and AI expertise, while directly contributing to patient care and innovation.
PharosAI offers more than a job—it offers a mission. You\’ll be part of a forward thinking, interdisciplinary team building a federated, secure AI platform designed to support NHS delivery, AI-driven drug discovery, and real-world clinical application. You\’ll also help lead the way in fair, transparent data sharing, patient involvement, and education in AI for healthcare professionals.
This is your chance to contribute to one of the most visionary cancer innovation projects in the UK—and make a real difference. This role is part of multiple exciting roles that we are recruiting into across a variety of disciplines for this project.
About you
For this role you will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and appropriate clinical knowledge in oncology and histopathology. You will be innovative, with high standards of accuracy and analysis.
For all our roles we are searching for those who will be passionate about contributing to cutting-edge cancer research and AI-driven innovation, with either or both capable technical backgrounds and collaborative mindsets, and a commitment to delivering or supporting excellence in research and the impact this can have on our society.
The project will be based at the Barts Cancer Institute, part of the Faculty of Medicine and Dentistry.
About the Institute
The Barts Cancer Institute (BCI) is a Cancer Research UK Centre of Excellence whose work aims to transform the lives of those with and at risk of cancer through innovative research in the laboratory, in patients and in populations. BCI is internationally renowned in many areas of cancer research, and it combines ground-breaking basic research with the expertise of clinicians and clinician scientists. BCI is committed in supporting and developing future cancer researchers through its extensive postgraduate training
About Queen Mary
We continue to embrace diversity of thought and opinion in everything we do, in the belief that when views collide, disciplines interact, and perspectives intersect, truly original thought takes form.
We offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and campus facilities in addition to comprehensive staff benefits, found here
Queen Mary\’s commitment to our diverse and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly.
*As part of the application process, you will be required to answer specific questions. Depending on the number of applications received, we may do an initial shortlisting process based on this criterion only.
Closing Date
27/07/2025, 23:55
Clinical Research Fellow - PharosAI employer: Barts Cancer Institute, Queen Mary University London
Contact Detail:
Barts Cancer Institute, Queen Mary University London Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Clinical Research Fellow - PharosAI
✨Tip Number 1
Familiarise yourself with the PharosAI initiative and its goals. Understanding the project's mission to revolutionise AI-powered cancer care will help you articulate your passion for the role during interviews and networking opportunities.
✨Tip Number 2
Connect with current or former employees of the Barts Cancer Institute or those involved in the PharosAI project on platforms like LinkedIn. Engaging with them can provide valuable insights into the team culture and expectations, which can be beneficial for your application.
✨Tip Number 3
Stay updated on the latest advancements in AI and oncology. Being knowledgeable about recent breakthroughs and how they relate to the PharosAI project will demonstrate your commitment to the field and your readiness to contribute effectively.
✨Tip Number 4
Prepare to discuss your experience with machine learning techniques and histopathology in detail. Be ready to share specific examples of how you've applied these skills in previous roles, as this will showcase your expertise and suitability for the position.
We think you need these skills to ace Clinical Research Fellow - PharosAI
Some tips for your application 🫡
Understand the Role: Thoroughly read the job description for the Clinical Research Fellow position. Make sure you understand the key responsibilities, required qualifications, and the mission of the PharosAI initiative.
Tailor Your CV: Customise your CV to highlight relevant experience in histopathology, machine learning techniques, and oncology. Emphasise any previous work that aligns with AI-driven cancer research and innovation.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for cancer research and AI. Discuss how your background and skills make you a perfect fit for the role and how you can contribute to the PharosAI project.
Prepare for Specific Questions: Be ready to answer specific questions as part of the application process. Think about how your experiences relate to the goals of the PharosAI initiative and prepare examples that demonstrate your expertise and commitment.
How to prepare for a job interview at Barts Cancer Institute, Queen Mary University London
✨Showcase Your Passion for Cancer Research
Make sure to express your enthusiasm for cutting-edge cancer research and AI-driven innovation. Share specific examples of how your previous work aligns with the mission of PharosAI and how you can contribute to their goals.
✨Demonstrate Your Technical Expertise
Be prepared to discuss your relevant PhD and medical degree, as well as your experience in histopathology and machine learning techniques. Highlight any projects where you've successfully applied these skills, especially in oncology.
✨Emphasise Collaboration and Interdisciplinary Work
Since the role involves working within a diverse team, illustrate your ability to collaborate effectively. Share experiences where you've worked with professionals from different disciplines and how that contributed to successful outcomes.
✨Prepare for Questions on Data Sharing and Ethics
Given the focus on fair and transparent data sharing, be ready to discuss your views on ethical considerations in AI and healthcare. Think about how you would approach patient involvement and education in this context.
