Machine Learning Researcher
Munich
Proxima Fusion
Proxima is a European fusion energy start-up building stellarator fusion power plants.
WHO WE ARE 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.
We're on a journey to redefine the energy landscape, ensuring a sustainable future for generations to come.
YOUR IMPACT
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.
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.
We're on a journey to redefine the energy landscape, ensuring a sustainable future for generations to come.
YOUR IMPACT
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.
WHY JOIN PROXIMA FUSION
- You will get to work on some of the most complex tech challenges to bring abundant, safe, clean energy to the world
- You'll get to join and learn from an exceptional selection of accomplished and driven individuals
- Do your life’s best work and enjoy the journey
- Get to show that big things are possible in Europe when you assemble the best talent
WHAT YOU WILL DO
- 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.
WHO YOU ARE
- We are looking for high performers that love challenges and see these as learning opportunities.
- It is important not to be afraid to experiment, take risks and learn from mistakes. We believe in contentious iterations and getting things done.
- A PhD in machine learning, computer science, physics, mathematics, or equivalent experience.
- 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 environments.
INTERVIEW PROCESS
- Recruiter Interview (30-60 min
- Technical Screening (30 min)
- Technical Panel (3x60 min)
- CEO call (30 min)
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Job stats:
27
3
0
Categories:
Machine Learning Jobs
Research Jobs
Tags: Computer Science Engineering Industrial Machine Learning Mathematics PhD Physics Prototyping Python
Perks/benefits: Career development
Region:
Europe
Country:
Germany
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