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Join our team as a VP of AI and help virtualize biological experiments to accelerate discovery!
About Turbine
Turbine is building Virtual Assays—AI-powered predictive models that can run biological experiments in silico. We're combining deep learning with a systematic approach to biology to enable faster, cheaper, more extensive testing. Our team is small, focused, and composed of researchers and engineers who care deeply about getting biology right.
We're seeking an experienced VP of AI to lead Turbine's AI and computational biology efforts as we scale our Virtual Assay platform. In this role, you'll build and mentor a world-class team, guide technical strategy, and ensure our AI capabilities remain at the forefront of the field.
Your core mission: ensure we can scale reliable, reproducible Virtual Assay capabilities while continuously deepening our understanding of biology and improving our competitive position in the AI-driven biology space.
Key Responsibilities
- Build and maintain a healthy, well-staffed AI team equipped to deliver current products and anticipate future needs
- Coach and develop your department to operate seamlessly as part of a modern product organization
- Ensure all work streams are clearly connected to Virtual Assay development and that we extract learnings from each initiative
- Partner with our Lab team to streamline data flow—ensuring up-to-date data requests, efficient handoffs, and that generated data feeds productively into model development
- Drive the strategic direction of Virtual Assay development to position us as a differentiated, valuable player in the market
- Collaborate with our CTO to guide internal development toward a general virtual cell capable of zero-shot assay prediction
- Represent Turbine at international conferences and contribute to our visibility as a leader in AI-driven biology
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.
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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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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.
You are a Turbiner if these personality traits apply to you
- You have self-awareness and strong intention on personal growth
- You seek out feedback and learn from mistakes and apply what you learned
- You take responsibility and focus on the outcomes over tasks
- You focus on shared success and are open to challenging others respectfully to get the best possible outcome
- You are in it for the long haul and have passion for our mission


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What We're Looking For
You bring a combination of technical depth, leadership experience, and professional visibility in the AI community:
- Strong people leadership skills; ability to build trust, develop talent, and create a high-performing culture
- Direct experience building or working with AI inference tools at production complexity
- Established credibility and network in the AI in drug discovery space
- Strategic thinking about where AI creates real value, both in research and in commercial applications
- Comfort operating at the intersection of AI, biology, and product; you don't need to be a computational biologist, but you must be curious and capable of learning the domain
Nice to Have
- Prior experience scaling AI teams or shipping AI products in regulated industries
- Exposure to or understanding of biological assays, phenotyping, or drug discovery
- Track record of publishing or speaking at major AI/ML conferences
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