
Bactobio is a biotechnology company focused on unlocking the potential of unculturable microbes through genomics, machine learning, and bioengineering. Their innovative approach aims to discover…

Bactobio is a biotechnology company focused on unlocking the potential of unculturable microbes through genomics, machine learning, and bioengineering. Their innovative approach aims to discover…
Headquarters: London, United Kingdom
Founded: 2020
Focus: Culturing unculturable soil microbes to discover natural products (antimicrobials/biofungicides) using synthetic biology, sequencing, and ML
Employees (approx.): ~54
Most recent funding: Convertible Note, Dec 1, 2022
Antimicrobial discovery, agricultural biofungicides, and sustainable biotechnology.
2020
Biotechnology Research
Most recent disclosed round per Crunchbase; company reported multiple rounds (three) overall.
“Has multiple institutional and individual backers including Bridford Group, Hugh Grant, Peder Nielsen, Pioneer Fund, Entangle S.A., Leopoldo Zambeletti, Jonathan Milner”
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We are looking for a PhD intern to help develop agentic workflows to drive insight in bioinformatics and metabolomic chemistry.
Company
Bactobio is a London biotech startup. We work to solve the antimicrobial resistance crisis across healthcare and agriculture by producing the next generation of market-leading antimicrobials. Since inception in 2020, Bactobio has built a deeptech platform that combines AI, synthetic biology, and multiomics to routinely discover new antimicrobial classes from nature. Our antimicrobial platform is fully operational, and we now successfully target the worst diseases and build portfolios of new, safe, and effective antimicrobial classes that bypass resistance that we then move towards commercialisation.
Our culture is built around impact, empowerment, and collaboration. We attract incredible scientists from world-leading institutions, mix them with operational experts, and provide guidance through industry leaders acting as mentors. We strongly believe that diversity combined with open and inclusive conversations lead to better solutions. As a result, we have created a collaborative work environment, where ambitious people enjoy working together to make the world greener and safer.
Role
We are looking for passionate and driven PhD students whose doctoral program includes a funded industry internship and who want to experience life inside a dynamic biotechnology start-up. These are fully immersive, on-site placements at our London office and laboratories, lasting a minimum of three months.
In this role, you’ll design and build agentic LLM workflows that support decision-making in bioinformatics and metabolomic chemistry at Bactobio, using the latest capabilities in modern AI.
With plenty of support from our Bioinformatics amp; Machine Learning team, you’ll contribute Python code to turn messy scientific questions and tradeoffs into reliable workflows, combining frontier LLMs with our proprietary biological data to produce recommendations scientists can use and trust.
You’ll have scope to explore workflow architecture and tool use, prompt and instruction design, and quality evaluation with benchmarking, testing, and iteration; all in a real scientific environment.
This is an applied research role with an opportunity to ship real code. Expect to see your work integrated into our production platform and used daily by our scientists to speed up analysis, improve decision quality, and move the company forward in tangible ways.
Our previous interns come from a range of programmes, including PIPS, iCASE, and MRC LID.
Team
You’ll be joining a vibrant, tight-knit, and highly collaborative team of about fifty people. We sit and work together and take genuine interest in one anothers work. Day-to-day, you’ll collaborate with wet-lab and automation scientists, data scientists, bioinformaticians, and software engineers, with plenty of exposure to the broader company journey too.
Everyone who writes code at Bactobio contributes regularly to the same shared codebase. We care about well-designed data models, best practices with sensible implementations, and building a tech stack that’s productive, maintainable, and genuinely enjoyable to work in.
Benefits
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