Serova
ML engineer / computational biologist

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About Serova
Serova builds personalized cancer vaccines. Each vaccine is made for the individual patient from their own samples and given in partnership with their treating physician. Each patient's vaccine is designed computationally, by models and agents that our team builds and trains.
The Role
Our research engineering team builds agents for biology and trains the models we use to design each patient's therapy. You'll build and ship those models and agents.
What You'll Work On
- HLA binding and antigen presentation
- Immunogenicity prediction
- Neoantigen ranking and selection for each patient
- mRNA sequence design
- Liquid biopsy models: ctDNA and tracking disease over time
- Patient response models: who responds, and why
- Tumor microenvironment modeling
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Who You Are
- An ML engineer or computational biologist who ships, not just trains
- You can take a messy biological problem, frame it, build the model and put it in front of the people who use it
- High agency, friendly and low ego
- Curious about biology
Requirements
- An MSc or PhD in computational biology, machine learning or a related field
- 2+ years of industry experience in computational biology or applied ML
- Strong Python and a modern deep learning stack (PyTorch or JAX)
- Based in the San Francisco Bay Area or London, or willing to relocate
- Authorized to work in the US or UK, or a realistic path to get there


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What Will Make You Stand Out
- Applied ML research at an AI-for-biology company
- Computational biology grounding: you work directly with biological data and wet lab collaborators
- Protein, peptide, sequence or immunology models
- LLM agents: you've built agents or tool-using systems that do real work
- You've taken a prototype to something people rely on
- Publications or open-source work that others use
Details
- Location: San Francisco or London
- Type: Full-time
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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