Senior Machine Learning Researcher

At Proxima Fusion, we're driven by a bold mission – to redefine the future of sustainable energy. Our unique concept, built upon the groundbreaking W7-X stellarator and the latest advances in technology, paves the way for commercially viable fusion power plants.

Our work in stellarator optimization, powered by cutting-edge computation and machine learning, is propelling us into uncharted territories of fusion technology. New higher performance design points are unlocked by high temperature superconducting magnets and we're leveraging this technology with advanced computational design capabilities.

We're on a journey to redefine the energy landscape, ensuring a sustainable future for generations to come.

At Proxima Fusion, you will join a diverse and interdisciplinary team working at the frontier of fusion technology. As an ML Researcher, you will work collaboratively with fusion scientists, engineers, and ML experts to integrate advanced ML techniques into stellarator optimization and engineering, transforming prototypes into production-ready solutions. Your contributions will, establish best practices for ML, and foster collaboration with academic and industrial partners. Join us to apply your knowledge and experience to solving real-world problems, helping to build stellarators that will power the future of clean energy.

• A PhD in machine learning, computer science, physics, mathematics, or equivalent experience.
• 3 years of experience with ML Frameworks such as PyTorch, Tensorflow, or Jax, and MLOps tooling.
• A specialization in geometric learning, generative and latent-space models, graph-based models, data-driven optimisation, or uncertainty quantification.
• Professional experience with applying ML to problems in the physical world, preferably in an inter-disciplinary setting.
• Strong knowledge of Python software development and the PyData ecosystem.
• Familiar with deployments in cloud enviroments.

• Identifying and defining novel ways to apply ML for stellarator optimization and engineering together with world-leading domain experts.
• Pursuing our real-world applications of ML from the prototyping stage to tools that are routinely used across the team.
• Maintain an active engagement with the broader ML community and ensure that we develop best-in-class ML solutions for the domain of fusion science and engineering.
• Brining together domain experts, including engineers and physicists, to drive and lead Machine Learning initiatives.

• Fulfilling Mission: Embark on a mission-driven journey at the forefront of fusion R&D, contributing to the development of groundbreaking energy solutions.
• Celebrating Success: Experience recognition with VSOPs, adding an extra touch of appreciation for your valuable contributions. Join us at Proxima Fusion and thrive in a supportive and rewarding environment!
• Work-Life Harmony: Enjoy a generous 30 vacation days, prioritising your well-being and creating a healthy work-life balance.
• Continuous Learning: Access language classes budget, fostering your personal development and expanding your skill set.
• Convenient Commuting: Receive a Deutschland ticket, ensuring stress-free and sustainable travel to and from work.
• Joyful Work Atmosphere: Indulge in delightful company cake and coffee during social hours, fostering a vibrant and enjoyable workplace. Join us at Proxima Fusion and thrive in a supportive and rewarding environment!

Proxima Fusion is firmly committed to fostering an inclusive and diverse work environment. We embrace the principles of equality and stand against discrimination on the basis of age, disability, gender, race, religion or belief, gender reassignment, marriage/civil partnership, pregnancy/maternity, or sexual orientation.

Our organizational culture values and promotes equal opportunities for everyone, recognizing that a diverse team brings a richness of perspectives and contributes to our overall success. We encourage and welcome applications from candidates with various backgrounds, talents, and potential. Our selection process is solely based on individual merit, ensuring fair and impartial consideration for all applicants.