At a Glance
- Tasks: Join us to develop cutting-edge machine learning models for materials science experimentation.
- Company: Matterhorn Studio is revolutionising Bayesian Optimisation in material science.
- Benefits: Enjoy a hybrid work environment with flexible options across the UK.
- Other info: Opportunity to publish your research and collaborate with industry leaders.
- Why this job: Be part of a pioneering team shaping the future of science and technology.
- Qualifications: MSc/PhD in Machine Learning with expertise in Bayesian Optimisation required.
The predicted salary is between 48000 - 72000 £ per year.
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:
- Researching the right Bayesian Optimisation techniques for a variety of experimentation challenges: multi-fidelity, multi-source, multi-step (generally known as 'grey-box' methods).
- 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.
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 jakob@matterhorn.studio with a CV and a few ideas of who you’d approach the above work.
Machine Learning Scientist (Open) employer: Matterhorn
At Matterhorn Studio, we pride ourselves on fostering a collaborative and innovative work culture that empowers our Machine Learning Scientists to push the boundaries of material science. With a strong focus on employee growth, we offer opportunities for research publication and hands-on experience in cutting-edge projects, all while enjoying the flexibility of a hybrid work environment in vibrant locations like Oxford and London. Join us to be part of a forward-thinking team that values your contributions and supports your professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist (Open)
✨Tip Number 1
Familiarise yourself with the latest advancements in Bayesian Optimisation. Attend webinars, read recent research papers, and engage in online forums to deepen your understanding. This will not only enhance your knowledge but also give you talking points during interviews.
✨Tip Number 2
Network with professionals in the materials science and pharmaceuticals sectors. Join relevant LinkedIn groups or attend industry conferences to connect with potential colleagues. Building these relationships can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to discuss practical applications of your work in Bayesian Optimisation. Think about specific projects where you've implemented these techniques and be ready to explain your approach and results. This will demonstrate your hands-on experience and problem-solving skills.
✨Tip Number 4
Showcase your passion for machine learning and its impact on material science. Be prepared to share your vision for how you can contribute to the team at Matterhorn Studio. A genuine enthusiasm for the field can set you apart from other candidates.
We think you need these skills to ace Machine Learning Scientist (Open)
Some tips for your application 🫡
Understand the Role:Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Scientist position. Familiarise yourself with Bayesian Optimisation techniques and how they apply to materials science.
Tailor Your CV:Highlight your relevant experience in Machine Learning and specifically in Bayesian Optimisation. Include any projects or research that demonstrate your skills and knowledge in this area.
Craft a Compelling Cover Letter:Write a cover letter that not only showcases your qualifications but also expresses your enthusiasm for the role. Mention specific techniques or ideas you would like to explore in the context of the job description.
Follow Up:After submitting your application, consider sending a polite follow-up email to express your continued interest in the position. This can help keep your application top of mind for the hiring team.
How to prepare for a job interview at Matterhorn
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Bayesian Optimisation in detail. Bring examples of past projects where you've successfully implemented machine learning models, especially in the context of materials science or similar fields.
✨Understand the Company’s Vision
Research Matterhorn Studio and their approach to Bayesian Optimisation. Familiarise yourself with their current projects and how they aim to innovate in material science. This will help you align your answers with their goals during the interview.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges or case studies related to multi-fidelity or grey-box methods. Practice articulating your thought process clearly, as this will demonstrate your analytical skills and ability to tackle complex problems.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, ongoing projects, and future directions of the company. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
