Machine Learning Scientist (Open)

Matterhorn; Greater London; Hybrid; GBP 40,000 - 60,000; Full time

Job summary

An innovative firm is seeking a Machine Learning Scientist with expertise in Bayesian Optimisation to join their team. This role involves collaborating with scientists in the materials space to develop machine learning models that optimize laboratory experimentation. You will have the chance to research and implement cutting-edge techniques, ensuring usability and interpretation for industry partners, particularly in pharmaceuticals. This position offers the opportunity to validate your models and contribute to significant research challenges, potentially leading to publications. Join a forward-thinking company that is shaping the future of material science through peer-reviewed methodologies.

Qualifications

• Experience in Machine Learning and Bayesian Optimisation at MSc/PhD level is essential.
• Strong research skills to tackle complex experimentation challenges.

Responsibilities

• Research and implement Bayesian Optimisation techniques for experimentation.
• Validate models and tackle deeper research challenges with publication opportunities.

Skills

Machine Learning

Bayesian Optimisation

Research Skills

Data Analysis

Education

MSc in Machine Learning

PhD in Machine Learning

Job description

Machine Learning Scientist (General Interest)

Date: Aug 1, 2024

We are looking for a Machine Learning Scientist in Bayesian Optimisation.

You will be working closely 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.

Responsibilities:

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).
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.

Minimum 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 [e-mail] with a CV and a few ideas of who you’d approach the above work.