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 to identify, implement and test models for concrete sciences, e.g. as described in https://arxiv.org/abs/2310.18288

You work will focus on:

1. 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)

2. Implementing these models for partners in the pharmaceuticals industry, focusing on ease of usability and interpretation

3. Validating the effectiveness of the models and tackling deeper research challenges, with the opportunity to publish.

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 see 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.