Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the application of machine learning to real-world biological workflows.
- Company: A growing tech organisation at the forefront of machine learning and biology.
- Benefits: Competitive salary, mentorship opportunities, and a chance to shape scientific direction.
- Why this job: Make a real impact by translating complex data into actionable insights.
- Qualifications: PhD or MSc in relevant fields with industry experience in ML and biology.
- Other info: Dynamic role with opportunities for career progression and collaboration.
The predicted salary is between 48000 - 72000 £ per year.
We have an exciting opportunity within a growing technology-led organisation applying advanced machine learning to complex biological and scientific data. The focus is on translating foundational models into practical, real-world workflows that support discovery, development, and decision-making in highly technical environments.
As a Senior Computational Scientist, you will provide scientific leadership at the intersection of biology and machine learning, ensuring applied work remains grounded in real-world challenges while delivering outputs that are usable, interpretable, and impactful.
This role will offer you:
- A senior individual contributor role with clear influence over scientific direction
- Ownership of applied model evaluation and real-world use cases
- Close collaboration with research, product, and commercial-facing teams
- The opportunity to mentor junior scientists and shape best practices
- Exposure to cutting-edge ML methods applied to complex biological data
- Scope to progress into people or technical leadership as the team scales
Your responsibilities will include:
- Leading the application and evaluation of foundation models in real-world scientific workflows
- Ensuring scientific rigor and relevance across applied modelling efforts
- Acting as a key scientific partner to research and engineering teams
- Translating complex biological and ML concepts into clear, actionable insights
- Supporting and mentoring junior team members
- Collaborating with product and business-facing teams to turn research outputs into deliverables
You will bring:
- PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field with industry experience or MSc in a relevant field with substantial industry experience applying ML to biological data
- Experience with single-cell
- Strong understanding of ML/AI methods for biological datasets (e.g. transformers, VAEs, diffusion models, classical ML)
- Hands-on experience with modern ML frameworks such as PyTorch or equivalent
- Ability to communicate complex scientific ideas to both technical and non-technical audiences
- Comfort operating in fast-paced, iterative environments
- A strong interest in building at the intersection of biology and machine learning
Senior Computational Scientist employer: BioTalent
Contact Detail:
BioTalent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Computational Scientist
✨Tip Number 1
Network like a pro! Reach out to professionals in the field of computational biology and machine learning. Attend meetups, webinars, or conferences where you can connect with potential employers and showcase your expertise.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your projects and contributions in applying ML to biological data. This will give you an edge when discussing your experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of ML methods and their applications in biology. Be ready to discuss how you've tackled real-world challenges in your previous roles.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you. Make sure to tailor your application to highlight your leadership and mentoring experiences, as well as your collaborative spirit.
We think you need these skills to ace Senior Computational Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences that align with the Senior Computational Scientist role. Highlight your expertise in machine learning and any relevant projects you've worked on, especially those involving biological data.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about the intersection of biology and machine learning. Share specific examples of how you've applied ML methods in real-world scenarios and how you can contribute to our mission at StudySmarter.
Showcase Your Communication Skills: Since you'll be translating complex concepts for various audiences, demonstrate your ability to communicate clearly in your application. Use straightforward language and avoid jargon where possible to show us you can make science accessible.
Apply Through Our Website: We encourage you to apply directly through our website. This ensures your application gets to the right people quickly and allows us to keep track of all applicants efficiently. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at BioTalent
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning methods, especially those relevant to biological datasets. Be ready to discuss your experience with models like transformers and VAEs, and how you've applied them in real-world scenarios.
✨Showcase Your Leadership Skills
As a Senior Computational Scientist, you'll be expected to lead and mentor. Prepare examples of how you've guided junior scientists or collaborated with cross-functional teams. Highlight your ability to translate complex concepts into actionable insights.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise. Practice explaining your work with modern ML frameworks like PyTorch. Be ready to discuss specific projects where you've evaluated foundation models and their impact on scientific workflows.
✨Communicate Clearly
You'll need to convey complex ideas to both technical and non-technical audiences. Practice simplifying your explanations without losing the essence of your work. This will show your ability to bridge the gap between science and application.
