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- Tasks: Design and develop machine learning models for cancer care using real-world patient data.
- Company: Stealth-stage medtech company revolutionising oncology with advanced AI.
- Benefits: Flexible contract with potential for full-time, work on impactful projects.
- Why this job: Join a world-class team tackling high-impact healthcare challenges with cutting-edge technology.
- Qualifications: Strong machine learning background and experience with healthcare data required.
- Other info: Dynamic environment with opportunities to shape a high-growth company.
The predicted salary is between 60000 - 80000 £ per year.
Location: Remote (Contract)
Duration: 3–6 month contract (with potential to convert to full-time)
Company: Stealth-stage MedTech (AI in Oncology)
About the Company
Our client is rapidly scaling, stealth-stage medtech company applying advanced AI to transform cancer care. Founded in late 2025 and led by experienced operators and researchers, we are building proprietary, data-driven models to improve cancer surveillance, diagnosis, and treatment decision-making. Our work is powered by rich longitudinal patient datasets, with strong in-house expertise in genomics. We are not focused on traditional imaging AI—instead, we tackle complex, multimodal clinical data to drive real-world impact in oncology.
The Opportunity
We are looking for exceptional AI Researchers / ML Engineers to join us on a high-impact contract basis (3–6 months) to accelerate model development across large-scale patient datasets. You will work closely with our Head of AI and core research team, contributing to the design, development, and deployment of models for:
- Risk prediction
- Patient outcome modeling
- Clinical decision support
High-performing contractors will be considered for full-time roles as we expand our team in Boston later this year.
What You’ll Do
- Design, build, and evaluate machine learning models on large-scale longitudinal patient datasets (e.g., EHR)
- Develop models for risk stratification and outcome prediction in oncology
- Work with multimodal data (clinical, genomic, and other structured/unstructured sources)
- Own the end-to-end ML lifecycle: data processing, experimentation, validation, and deployment
- Collaborate closely with cross-functional teams including AI researchers, engineers, and domain experts
- Translate research insights into production-ready systems
What We’re Looking For
Core Requirements
- Strong background in machine learning and ML engineering
- Experience working with real-world healthcare data, especially:
- Electronic Health Records (EHR)
- Longitudinal patient datasets
Preferred / Differentiators
- Experience with genomics or multimodal biomedical data
- Track record of publications in top-tier venues (e.g., NeurIPS, ICML, ICLR, Nature, Science)
- Experience in healthcare AI, medtech, or clinical data environments
- Background in statistical modeling, causal inference, or time-series analysis
Who You Are
- A hands-on builder who can move quickly from idea → experiment → production
- Comfortable working in a fast-paced, early-stage environment
- Able to balance research depth with engineering execution
- Motivated by applying AI to high-impact problems in healthcare
Why Join Us
- Work on cutting-edge AI problems in cancer care with real-world impact
- Access to proprietary, high-quality patient datasets
- Collaborate with a world-class AI and genomics team
- Flexible contract structure with clear path to full-time
- Join early and help shape a high-growth company pre-public launch
Researcher - Financial Services employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Researcher - Financial Services
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just reach out on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Show Off Your Skills
Don’t just talk about your experience; showcase it! Create a portfolio of your projects, especially those related to machine learning and healthcare data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Ace the Interview
Prepare for interviews by brushing up on common questions and scenarios specific to AI and healthcare. Practice explaining your thought process when tackling complex problems, as this will demonstrate your expertise and problem-solving skills.
✨Apply Through Our Website
Make sure to apply directly through our website for the best chance at landing that role! We love seeing candidates who are proactive and genuinely interested in joining our team.
We think you need these skills to ace Researcher - Financial Services
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Researcher in Financial Services. Highlight your experience with machine learning, especially in healthcare and oncology, and don’t forget to mention any relevant projects or publications!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about applying AI in healthcare and how your skills align with our mission. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any relevant projects, especially those involving large-scale patient datasets or machine learning models, make sure to include them. We love seeing real-world applications of your skills!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at DeepRec.ai
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals and be ready to discuss your experience with real-world healthcare data. Familiarise yourself with Electronic Health Records (EHR) and how they relate to the role, as this will show your genuine interest in the position.
✨Showcase Your Projects
Prepare to talk about specific projects you've worked on, especially those involving risk prediction or patient outcome modelling. Highlight your role in the end-to-end ML lifecycle and any challenges you faced, as this will demonstrate your hands-on experience and problem-solving skills.
✨Ask Smart Questions
Come prepared with insightful questions about the company's approach to AI in oncology and their current projects. This not only shows your enthusiasm but also helps you gauge if the company aligns with your career goals and values.
✨Be Ready for Technical Challenges
Expect to tackle some technical questions or even a coding challenge during the interview. Brush up on your programming skills, particularly in Python and frameworks like PyTorch or TensorFlow, so you can confidently demonstrate your technical prowess.