Computational Scientist

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CC Bio is an award-winning synthetic biology company, which has been a subsidiary of a clinical stage global parent company, Precisio Biotix Inc. since 2024. We are based in state-of-the-art facilities at the Imperial Translation and Innovation Hub (iHUB), West London.
At CC Bio, we discover, engineer and develop potent and specific antimicrobial enzymes for use as next generation therapeutics. By leveraging the combined power of systems biology, synthetic biology and microbiology, we are engineering this new class of efficacious enzymes to improve patient outcomes worldwide in the fight against antimicrobial resistance. We combine sophisticated and proprietary ML-based protein discovery and engineering platforms with high throughput screening capabilities, positioning us as a world leader in enzyme design.
Description of Your Role
We are seeking a motivated computational biologist to join the CC Bio team in August 2025 for a 24-month prestigious grant funded project. This role will be within a growing team at our London-based laboratory.
You will be an integral member of the experimental team, working closely with microbiologists and molecular biologists to facilitate the successful outcomes of this new grant project. The grant project aims to leverage our existing enzyme discovery and engineering platform (Zeus) to develop a novel class of enzyme-based therapeutic. These enzymes are hypothesised to disrupt the growth of key obligate anaerobic pathogens.
Your time will largely be based using and helping to further develop our AI-guided proprietary drug development platform, Zeus. You will leverage Zeus’s established functionality to discover candidate libraries for testing/development by the wider team, and re-integrate experimental data into Zeus to facilitate ML-based protein engineering strategies.
What You’ll Do in This Role
This role involves use and continued development of our cutting-edge proprietary candidate discovery and engineering software platform, Zeus for candidate identification. Specifically, your part of the project programme will cover the following areas:

• You will discover and engineer new peptide-based therapeutics capable of augmenting the microbiome using our proprietary In Silico discovery platform, Zeus.
  
• You will select appropriate candidates for synthesis by curating protein structure, predicted stability, and other proprietary metrics of lead candidate suitability presented from the Zeus platform.
  
• You will generate derivatives of these candidates using ML-guided proprietary computational tools previously developed and implemented on the Zeus platform.
  
• You will lead integration of experimental data into Zeus to optimise candidate selection and prioritisation processes.
  
• You will work in our software development team, building cutting-edge functionalities for Zeus.
  
• You will keep excellent experimental/data records to convey project results accurately and facilitate publication upon project completion.
  Requirements
  
• You have at least an MSc degree, or preferably, a PhD degree in computational biology, bioinformatics, computer science, data science, synthetic biology or similar.
  
• You have experience working with large biological datasets and are comfortable manipulating these packages to identify hits for wet lab activity assessments. In particular, you will have knowledge of commonly used bioinformatics software and statistical models.
  
• You have experience with machine learning techniques and large language model utilisation.
  
• You understand higher-order protein structure, and are comfortable with conducting in silico design of next-generation protein candidates from wild-type templates through use of tools (AlphaFold, BLAST, MSA etc.)
  
• You are proficient in Python and feel comfortable troubleshooting day-to-day issues with computational platforms. Experience with modern software development techniques (TDD, git, CI/CD), and cloud server usage is desirable.
  
• You are familiar and comfortable using cloud-based infrastructure.
  
• You can independently curate literature and design experiments in an autonomous fashion.
  Additional, But Not Essential, Skills: “Nice to Haves”
  
• You have previously worked in a commercial biotechnology environment.
  How You Enjoy Working
  
• You enjoy conceiving interesting ideas, discussing them, and then putting them into action yourself.
  
• You actively seek to collaborate to solve problems, and have no problem working with people who have different viewpoints and backgrounds.
  
• You don’t take constructive criticism personally and understand that in scientific research, the results of your work do not always represent your efforts.
  
• You like to work on meaningful projects, and more generally, be part of businesses which are focused on human health research.
  
• You will receive a fixed, competitive salary for the duration of the 24-month project. This is based upon annual full-time salary which will be commensurate with degree level/experience. The Imperial College London salary scale is used as a comparator by the company for salary determination.
  
• You will be embedded in a fully equipped laboratory at the Imperial College London Translation and Innovation Hub, within a vibrant academic community.
  
• You will work within an organisation with a generally flexible working culture and will receive a generous leave allowance.
  Our company culture is, and will always be, inclusive: we will not discriminate based upon gender identity, race, nationality, skin colour, age, disability, relationship status, sexual orientation, or any other legally protected right or status.
  If this job role is a good fit for your skillset, please get in touch with [emailprotected] before June 17th, 2025 including the term “BMGF-C” in your email subject title. Don’t be discouraged from applying if your skills do not exactly align with the requirements, but you feel that you would still succeed in the role. In your application, please include your CV alongside a cover letter which outlines why you’d like to join us.
  
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