Clinical Research Fellow - PharosAI

Clinical Research Fellow - PharosAI

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
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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: Applications are open until 27/07/2025; reasonable adjustments for candidates with disabilities.

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

At Queen Mary University of London, we pride ourselves on being an exceptional employer, particularly within the innovative PharosAI initiative. Our commitment to fostering a diverse and inclusive work culture is complemented by flexible working arrangements and comprehensive staff benefits, ensuring that our employees can thrive both personally and professionally. Joining us means becoming part of a pioneering team dedicated to revolutionising cancer care through cutting-edge research and technology, with ample opportunities for growth and collaboration in a supportive environment.
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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 and alignment with their vision during interviews.

✨Tip Number 2

Network with professionals in the field of oncology and AI. Attend relevant conferences or webinars where you can meet current researchers and practitioners, as this could lead to valuable insights and connections that may support your application.

✨Tip Number 3

Prepare to discuss your recent track record in histopathology and machine learning techniques. Be ready to provide specific examples of how you've applied these skills in your previous work, showcasing your innovative approach and high standards of accuracy.

✨Tip Number 4

Demonstrate your commitment to collaborative research. Highlight any past experiences where you've worked in interdisciplinary teams, as this role values a collaborative mindset and the ability to contribute to cutting-edge cancer research.

We think you need these skills to ace Clinical Research Fellow - PharosAI

PhD in a relevant field
Medical degree
GMC registration at Specialist Registrar Grade or below
Histopathology expertise
Machine learning techniques
Clinical knowledge in oncology
Data analysis skills
Attention to detail
Strong communication skills
Collaborative mindset
Innovation and creativity
Commitment to research excellence
Understanding of AI applications in healthcare
Ability to work in interdisciplinary teams
Passion for cancer research

Some tips for your application 🫡

Understand the Role: Read the job description thoroughly to grasp the responsibilities and requirements of the Clinical Research Fellow position. Highlight your relevant experience in histopathology and machine learning techniques.

Tailor Your CV: Customise your CV to reflect your qualifications, particularly your PhD and medical degree. Emphasise your recent track record in oncology and any innovative projects you've been involved in.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for cancer research and AI-driven innovation. Mention specific examples of how your skills align with the mission of the PharosAI initiative.

Prepare for Application Questions: Be ready to answer specific questions as part of the application process. Think about how your experiences relate to the goals of the project and prepare concise, impactful responses.

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 in a clinical setting.

✨Emphasise Collaboration and Interdisciplinary Work

Since the role involves working within a diverse team, illustrate your ability to collaborate effectively with scientists, bioinformaticians, and other professionals. Share examples of past teamwork experiences that led 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 AI for healthcare professionals.

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