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Machine Learning Scientist (Material Simulation)

Materials Nexus
London
9 months ago
Applications closed

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Job Description

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

As a Machine Learning Scientist, you will join a team focused on the intersection of ML and Material Science. Our ambition is to apply ML across our materials discovery platform to make the most substantial impact possible.

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! 

As a part of this role, you’ll get to:

  • Contribute to the design and implementation of state-of-the-art scaleable and performant MLIPs suitable for high-throughput materials simulations, for example using equivariant GNNs

  • Collaborate with our science team to accelerate our materials discovery pipeline using ML, more experienced candidates could also be influencing product roadmaps

  • Interface with large volumes of simulation data (generated in-house) to build and refine foundational models

  • Apply best practices throughout the model lifecycle, from experimentation to deployment

  • Shape the role and take on broader responsibilities based on interest and experience


Qualifications

What we think you will need to be successful:

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 machine-learning models to accelerate materials simulations (e.g. creating a GNN for property prediction)

  • Experience building and deploying ML products in a team

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++



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.

Fully covered comprehensive private healthcare and mental health support.

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 30 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 to discuss a relevant topic in order to help us understand how you can make an impact.


Third step: A 90 minute in person meeting which will include a whiteboard exercise to break down a Machine Learning problem with the technical team, as well as an opportunity to meet with our wider team to better understand how we can work together. 

AI Futures Grant: 

We are proud to support talent from diverse locations and backgrounds. If successful, relocation may be available through the AI Futures Grant, enabling you to join us in the UK and contribute to our mission seamlessly.

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