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- Tasks: Join us to tackle complex biological challenges using AI and data science.
- Company: Be part of a cutting-edge life sciences company driving innovation in biology.
- Benefits: Enjoy flexible work options, collaborative culture, and opportunities for professional growth.
- Why this job: Make a real impact by translating data into insights that shape the future of healthcare.
- Qualifications: MSc or PhD in Computational Biology; strong Python skills and experience with single-cell data required.
- Other info: Ideal for those passionate about blending biology with technology in a fast-paced environment.
The predicted salary is between 36000 - 60000 £ per year.
We’re seeking a highly motivated computational biologist to partner with leading R&D teams in life sciences, applying advanced AI models to solve complex biological challenges. You’ll work at the interface of data science, biology, and product development — helping translate large-scale omics data into actionable insights for discovery and development. In this high-impact, fast-moving role, you’ll prototype with cutting-edge machine learning tools, rapidly moving from concept to insight. You’ll collaborate closely with engineering and product teams to shape and refine innovative solutions that address real-world biological problems.
Key Responsibilities
- Partner with scientific and technical teams to analyze complex biological datasets (e.g., transcriptomics, single-cell data)
- Apply and adapt machine learning models to address problems in discovery and development
- Rapidly prototype and iterate on computational approaches to generate insights
- Communicate findings clearly across technical and non-technical audiences
- Contribute to shaping data products and internal tools
Requirements
- Essential MSc or PhD in Computational Biology, Bioinformatics, or a related field
- Strong Python programming skills
- Experience working with single cell data
- Familiarity with recent machine learning methods relevant to omics data
- Understanding of modern AI/ML techniques (e.g., model fine-tuning, representation learning)
- Strong foundation in computational biology methods
- Ability to clearly articulate scientific findings to diverse stakeholders
- Customer- and product-focused mindset
Preferred
- Prior experience in industry (biotech, pharma, or related sectors)
- Contributions to open-source bioinformatics or computational biology tools
- Exposure to advanced model architectures (e.g., Transformers, sequence models, probabilistic models)
- Experience supporting discovery or development projects
Computational Biologist employer: Skills Alliance
Contact Detail:
Skills Alliance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computational Biologist
✨Tip Number 1
Network with professionals in the life sciences and computational biology fields. Attend relevant conferences, webinars, or meetups to connect with potential colleagues and learn about the latest trends and technologies in the industry.
✨Tip Number 2
Showcase your skills by working on personal projects or contributing to open-source bioinformatics tools. This not only demonstrates your expertise but also gives you practical experience that can set you apart from other candidates.
✨Tip Number 3
Familiarise yourself with the specific machine learning methods mentioned in the job description, such as model fine-tuning and representation learning. Being able to discuss these techniques confidently during interviews will highlight your readiness for the role.
✨Tip Number 4
Prepare to communicate complex biological concepts clearly to both technical and non-technical audiences. Practising how to present your findings in an accessible way will be crucial, as collaboration with diverse teams is a key part of the role.
We think you need these skills to ace Computational Biologist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your MSc or PhD in Computational Biology or Bioinformatics. Emphasise your Python programming skills and any experience with single-cell data, as these are essential for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for applying AI models to biological challenges. Mention specific projects where you've used machine learning methods relevant to omics data, showcasing your ability to communicate findings to both technical and non-technical audiences.
Showcase Relevant Experience: If you have prior industry experience in biotech or pharma, make sure to detail this in your application. Highlight any contributions to open-source bioinformatics tools or experience with advanced model architectures, as these will set you apart.
Demonstrate Your Problem-Solving Skills: Provide examples of how you've rapidly prototyped computational approaches to generate insights in previous roles. This will demonstrate your ability to work in a fast-moving environment and your customer-focused mindset.
How to prepare for a job interview at Skills Alliance
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills, especially in Python. Highlight any projects where you've applied machine learning models to biological datasets, particularly single-cell data, as this is crucial for the role.
✨Demonstrate Your Problem-Solving Ability
Think of specific examples where you've tackled complex biological challenges using computational methods. Be ready to explain your thought process and how you iterated on your approaches to generate insights.
✨Communicate Effectively
Practice explaining your findings in a way that can be understood by both technical and non-technical audiences. This will show your ability to bridge the gap between data science and biology, which is essential for the role.
✨Familiarise Yourself with Current Trends
Stay updated on recent advancements in AI/ML techniques relevant to omics data. Being able to discuss these trends and how they can be applied in the role will demonstrate your passion and knowledge in the field.
