Matterhorn Studio
Machine Learning Scientist (Open)

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Machine Learning Scientist (General Interest)
Aug 1, 2024
We are looking for a Machine Learning Scientist in Bayesian Optimisation.
You will be working closely together with scientists in the materials space to build machine learning models (OptApps) that will inform laboratory experimentation schedules, anywhere from complete-manual to fully self-driving.
Specifically, there will be an emphasis on identifying, implementing, and testing models for concrete sciences, e.g. as described in https://arxiv.org/abs/2310.18288.
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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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.
Your Work Will Focus On
- Researching the right Bayesian Optimisation techniques for a variety of experimentation challenges: multi-fidelity, multi-source, multi-step (generally known as ‘grey-box’ methods, see https://arxiv.org/abs/2201.00272)
- Implementing these models for partners in the pharmaceuticals industry, focusing on ease of usability and interpretation
- Validating the effectiveness of the models and tackling deeper research challenges, with the opportunity to publish.


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Requirements
You must have relevant experience in Machine Learning, specifically Bayesian Optimisation, at MSc/PhD level to complete the above work.
Location
Hybrid/Oxford/London (anywhere in the UK)
Matterhorn Studio is leading a paradigm shift towards peer-reviewed plug-in Bayesian Optimisation.
We’re looking forward to seeing how we can shape the future of material science together with you.
Contact Jakob at jakob@matterhorn.studio with a CV and a few ideas of who you’d approach the above work.
“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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