Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and develop machine learning models to transform 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, access to high-quality datasets, and collaboration with experts.
- Why this job: Make a real impact in healthcare by tackling cutting-edge AI challenges in cancer treatment.
- Qualifications: Strong machine learning background, experience with healthcare data, and programming skills in Python.
- Other info: Join a fast-paced team and help shape a high-growth company before its public launch.
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
Science researcher employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Science researcher
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and healthcare sectors on LinkedIn. Join relevant groups, attend virtual meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to healthcare data. Use platforms like GitHub to share your code and results. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with cross-functional teams. Mock interviews can help you feel more confident!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job postings and make sure your application stands out by tailoring it to the specific role and company culture.
We think you need these skills to ace Science researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience with machine learning and healthcare data. We want to see how your skills align with the role, so don’t be shy about showcasing 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 oncology and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any interesting projects, especially those involving EHR or multimodal data, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at DeepRec.ai
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals and any specific techniques relevant to oncology. Be ready to discuss your past projects, especially those involving real-world healthcare data like EHRs. This shows you’re not just a theorist but someone who can apply their knowledge practically.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex problems in your previous roles. Think of examples where you designed and deployed models, particularly in high-stakes environments. This will demonstrate your ability to handle the challenges that come with working in a fast-paced, early-stage company.
✨Collaborate Like a Pro
Since you'll be working closely with cross-functional teams, highlight your teamwork experiences. Share stories that illustrate your ability to communicate effectively with AI researchers, engineers, and domain experts. This will show that you can thrive in a collaborative environment.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to AI in oncology and their future plans. This not only shows your genuine interest in the role but also gives you a chance to assess if the company aligns with your career goals. Plus, it’s a great way to engage with your interviewers!