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- Tasks: Develop algorithms for DNA design and collaborate with scientists to optimise gene constructs.
- Company: Join a pioneering startup merging biology and technology to revolutionise DNA synthesis.
- Benefits: Enjoy a competitive salary, access to cutting-edge tools, and a budget for professional development.
- Why this job: Be part of a dynamic team making a real impact in the field of synthetic biology.
- Qualifications: Advanced degree in Computational Biology or related field; strong programming skills required.
- Other info: Hybrid work model available; ideal for those passionate about science and innovation.
The predicted salary is between 55000 - 70000 £ per year.
Location: Cambridge (Hybrid)
Join an early-stage startup at the intersection of code and biology, where DNA is the design language and synthesis is the platform. Their mission is to accelerate the design and synthesis of DNA – enabling researchers, developers, and engineers to treat biology as a programmable system. They are building a platform to streamline sequence design, optimise gene constructs, and scale high-throughput synthesis. The work sits at the intersection of machine learning, biological design, and molecular engineering.
About the Role
You’ll join a multidisciplinary team of scientists and engineers, contributing to the development of core algorithms, models, and tools that underpin technology.
What’s on offer:
- £65,000 - £80,000 base salary DOE
- Access to cutting-edge tools, datasets, and experimental infrastructure
- Budget for conferences, training, and professional development
- A collaborative, science-driven culture with direct impact on product and platform direction
Your Responsibilities:
- Develop and implement algorithms for sequence optimisation, codon usage, secondary structure prediction, and synthesis constraint resolution
- Build and maintain scalable pipelines for gene design and validation
- Analyse experimental results to refine computational models and improve design outcomes
- Collaborate closely with molecular biologists to integrate design and testing workflows
- Contribute to the development of internal tools, data infrastructure, and documentation
What you bring:
- Advanced degree (PhD or equivalent experience) in Computational Biology, Bioinformatics, Genomics, or related field
- Strong programming skills (Python preferred) and experience with scientific computing libraries
- Solid understanding of molecular biology, gene expression systems, and synthetic construct design
- Familiarity with genome-scale data, biological sequence analysis, or protein-coding gene optimisation
- Experience working in cross-functional teams and navigating the fast pace of early-stage R&D
Desirable (not essential):
- Experience with ML/AI in biological design
- Exposure to wet-lab workflows or automation platforms
- Contributions to open-source bioinformatics or synthetic biology tools
Please apply with a copy of your CV.
Computational Biologist employer: Cubiq Recruitment
Contact Detail:
Cubiq Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computational Biologist
✨Tip Number 1
Familiarise yourself with the latest advancements in computational biology and synthetic biology. This will not only help you understand the company's mission better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field by attending relevant conferences or workshops. This can provide you with insights into industry trends and may even lead to referrals or recommendations for the position.
✨Tip Number 3
Showcase your programming skills by contributing to open-source projects related to bioinformatics or synthetic biology. This demonstrates your practical experience and commitment to the field, making you a more attractive candidate.
✨Tip Number 4
Prepare to discuss specific algorithms or models you've worked on that relate to sequence optimisation or gene design. Being able to articulate your hands-on experience will set you apart from other candidates.
We think you need these skills to ace Computational Biologist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your advanced degree and relevant experience in Computational Biology, Bioinformatics, or Genomics. Emphasise your programming skills, particularly in Python, and any familiarity with scientific computing libraries.
Showcase Relevant Projects: Include specific projects or experiences that demonstrate your ability to develop algorithms for sequence optimisation and your understanding of molecular biology. Mention any contributions to open-source bioinformatics tools if applicable.
Highlight Collaboration Skills: Since the role involves working closely with molecular biologists, emphasise your experience in cross-functional teams. Provide examples of how you've successfully collaborated in fast-paced R&D environments.
Express Your Passion: In your application, convey your enthusiasm for the intersection of code and biology. Discuss why you are excited about the opportunity to contribute to a startup focused on programmable biology and how you can impact their mission.
How to prepare for a job interview at Cubiq Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your programming skills, especially in Python, and any relevant scientific computing libraries you've used. Highlight specific projects where you've developed algorithms or worked with genomic data.
✨Demonstrate Your Understanding of Biology
Make sure you can explain key concepts in molecular biology and synthetic construct design. Be ready to discuss how your knowledge can contribute to the company's mission of treating biology as a programmable system.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with molecular biologists, think of examples from your past experiences where you successfully collaborated in cross-functional teams. Emphasise your ability to navigate the fast pace of early-stage R&D.
✨Discuss Your Experience with ML/AI
If you have experience with machine learning or AI in biological design, be sure to bring it up. Discuss any relevant projects or contributions to open-source tools that demonstrate your capability in this area.
