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- Tasks: Lead transformative projects in data science and AI for biological research.
- Company: Join the Wellcome Sanger Institute, a leader in genomic research.
- Benefits: Enjoy hybrid work, competitive salary, and opportunities for global collaboration.
- Why this job: Make a real impact in cutting-edge research and advance your career.
- Qualifications: MSc/PhD in a quantitative field and strong Python skills required.
- Other info: Inclusive culture with a focus on diversity and professional growth.
The predicted salary is between 44905 - 63815 £ per year.
This role is for a Principal/Senior Data Scientist on a 2‑year contract, offering an annual salary of £44,905‑£63,815. It is located in a hybrid work environment in Hinxton, England, United Kingdom. Candidates should have expertise in machine learning, Python, and experience in computational biology or related fields.
About Us
We are hiring a Senior Data Scientist/Principal Data Scientist to join the interdisciplinary Lotfollahi Group at the Wellcome Sanger Institute. Our mission is to develop data‑driven and biologically grounded AI tools for decoding complex cellular systems. We collaborate closely with the Human Cell Atlas, Sanger’s single‑cell programs, and international leaders in the field.
Research Focus Areas
- Spatial & Multi‑omics Atlas Construction – Build large‑scale spatial and single‑cell atlases across diseased tissues (pancreas, kidney, skin, liver) using spatial transcriptomics, scRNA‑seq, and multi‑ome data.
- Generative AI for Cell Fate & Perturbations – Develop diffusion, flow‑matching, and transformer‑based generative models to predict cell fate, tissue remodelling, and drug or perturbation responses in silico.
- Foundational Models for Single‑Cell Biology – Train large, generalizable deep models across public and internal datasets to support the Human Cell Atlas and broad Sanger research programs.
- Open Targets Translational AI Projects – Apply foundational and multi‑omics models to real‑world challenges in drug discovery, target identification, and target safety in collaboration with major pharma partners.
- Agentic AI for Scientific Reasoning & Experiment Design – Develop AI agents capable of hypothesis generation, experiment planning, and multi‑step scientific workflows using reinforcement learning and tool‑use models.
- Core Machine Learning Research – Advance fundamental ML methods tailored for biological data, including advanced generative modelling, scalable training algorithms, representation learning, and uncertainty modelling.
- Multimodal Learning (Imaging + Genomics + Clinical Data) – Create models that integrate histopathology imaging, spatial proteomics, single‑cell genomics, and patient‑level clinical data.
Role Responsibilities
- Lead and manage transformative projects that integrate single‑cell genomics, spatial transcriptomics, and generative AI.
- Design, develop, and evaluate advanced ML models tailored to biological data.
- Translate complex scientific questions into computational solutions and present results to multidisciplinary teams.
- Provide scientific leadership in interdisciplinary research, supervising PhD students and postdoctoral fellows.
- Publish high‑impact papers and contribute to the open‑science community.
Essential Skills & Qualifications
- MSc and/or Ph.D. in a quantitative discipline (e.g., Computational Biology, Bioinformatics, Statistics, Physics, Computer Science).
- Proven experience in advanced statistical techniques, machine learning, and modern deep‑learning frameworks (PyTorch, TensorFlow, SciPy, Scikit‑Learn).
- Strong programming skills in Python and experience with software development best practices (git, code reviews, package management).
- Experience with cloud environments (Amazon AWS S3, EC2, etc.) and data‑management pipelines.
- Excellent communication skills, able to explain complex methods to non‑technical stakeholders.
- Ability to work in a fast‑changing environment, prioritize tasks, and deliver consistent results.
- Publications in peer‑reviewed journals or preprint archives on machine learning or its application to biology.
- Experience in supervising PhD students or postdocs and writing manuscripts for publication.
Application Process
Please submit your CV and a cover letter detailing your research experience, interest in the focus areas, and future aspirations. The application deadline is 8th February 2026.
Equality, Diversity and Inclusion
We are committed to creating an inclusive culture where everyone can thrive. We welcome applications from all backgrounds, and all decisions are made without discrimination.
Benefits
- Hybrid working arrangement with flexible working hours.
- Competitive salary and statutory benefits.
- Opportunities to publish and collaborate with leading researchers worldwide.
Principal/Senior Data Scientist employer: Data Freelance Hub
Contact Detail:
Data Freelance Hub Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal/Senior Data Scientist
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to data science. You never know who might be looking for someone with your skills or who can refer you to a great opportunity.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving machine learning and Python. Share your work on platforms like GitHub or even your own website. This gives potential employers a taste of what you can do!
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies. Be ready to discuss your past projects and how they relate to the role. Remember, it’s not just about technical skills; show your passion for the field too!
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Principal/Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and Python, as well as any relevant work in computational biology. We want to see how your skills align with our mission at StudySmarter!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your research experience, why you're interested in our focus areas, and what you hope to achieve with us. Keep it engaging and personal!
Showcase Your Communication Skills: Since you'll be explaining complex methods to non-technical folks, make sure to demonstrate your ability to communicate clearly in your application. We love candidates who can bridge the gap between science and storytelling!
Apply Through Our Website: Don't forget to submit your application through our website! It’s the best way for us to receive your materials and keep track of your application. Plus, we can't wait to hear from you!
How to prepare for a job interview at Data Freelance Hub
✨Know Your Stuff
Make sure you brush up on your machine learning and Python skills. Be ready to discuss specific projects you've worked on, especially those related to computational biology. This role is all about applying advanced techniques, so having concrete examples will show you're the right fit.
✨Show Your Passion for Biology
Since this position involves decoding complex cellular systems, demonstrate your enthusiasm for biology and how it intersects with data science. Talk about any relevant research or projects that highlight your interest in the field, especially in areas like single-cell genomics or spatial transcriptomics.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Brush up on advanced statistical techniques and deep learning frameworks like PyTorch or TensorFlow. Practising coding problems in Python can also help you feel more confident when tackling these questions.
✨Communicate Clearly
You’ll need to explain complex methods to non-technical stakeholders, so practice articulating your thoughts clearly. Use simple language to describe your work and be prepared to discuss how you would present your findings to a multidisciplinary team.
