Company Description

Materials contribute to 50% of the world’s CO2 emissions, those critical to the net-zero transition being the biggest culprits. Our AI platform leverages quantum calculations to model and design novel materials that are cheaper, higher performing and more environmentally friendly. We are accelerating materials discovery from decades to months.

Case study: https://www.materialsnexus.com/news/magnex-rare-earth-free-permanent-magnet

Recent press: https://www.popularmechanics.com/science/green-tech/a61147476/ai-developed-magnet-free-of-rare-earth-metals/

Job Description

At Materials Nexus, our mission is accelerate the change to net-zero through the disruption of materials discovery and production.

As Machine Learning Scientist you will play a role in collaborating with the wider ML team so our scientific platform can expand it’s capabilities at an even faster rate.

As the ML team grows, we are happy to consider candidates from all levels. Even if you do not think you are an exact fit for the role, but are passionate about our mission and work we’d still like to see your application!

What you will be doing:

Build and scale state-of-the-art ML models of materials, accelerating discovery of new materials while ensuring improved accuracy and reliability.
Collaborate with our science team to identify opportunities to enhance our platform and product offering, more experienced candidates could also be influencing product roadmaps
Apply data science and machine-learning to inferunderstanding from our datasets
Deploy best practices throughout the machine learning team, with potential to take on more responsibility depending on experience

Qualifications

We are looking for talented and, more importantly, passionate individuals who are motivated by the application of science and innovation to achieve net-zero materials.

Experience building and deploying ML products in a team
Experience applying machine-learning and data science techniques to materials simulations (e.g., use of PyTorch to train models of physical properties)

Nice to haves:

Experience deploying models in a cloud environment.
Understanding of containerisation technology (e.g., Docker).
Peer-reviewed publications on relevant topics.
Ability in JavaScript, Fortran, or C++.
Experience leading a high performing ML team (if interested)
Understanding of issues in material sustainability and commitment to addressing them.

Additional Information

Stock Options: We value our employees and you to share in the success of the company. You will be a vested partner in our future achievements.

Flexible holidays: 33 days annual leave/year which can be used on UK public holidays or on more convenient days for you.

Your birthday day off: Enjoy a well-deserved day off to celebrate and recharge.

✈️Work abroad: Travel the world while you get your job done - see family, or simply explore a new place!

Enhanced Family & Carers leave to ensure you get that quality time in when you need it

Flexible work arrangements: our shared office space in Shoreditch is here to help foster collaboration and community. Most of the team is in 2-3 days a week, but we are happy to discuss alternatives as necessary.

Continuous learning and growth: We’re pioneers in our field, so you'll be encouraged to expand your knowledge and skills in new areas too.

The process:

First step: A 45 minute video call with Julia, our People Associate, to learn a bit more about you and what you are looking for!

Second step: A 45 minute video call with our technical team - Get to know each other + short code review

Third step: Meet the technical team, in person. This will consist of a 90 minute coding and system design review.

Materials Nexus jobs

Machine Learning Scientist (Material Simulation)

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