Senior Analytical Design Engineer - Electrochemistry
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Ceres is a global leader in solid oxide technology, driving the clean energy revolution. Our steel-supported fuel cell and electrolyser technology gives partners a decade of development advantage, accelerating innovation in power generation, green hydrogen, and distributed power solutions for data centre's. Trusted by some of the world’s most progressive companies, our proven designs deliver efficient, low-cost solutions backed by over 5 million test hours. At Ceres, innovation is in our DNA. Join us and be part of a world-class team making a positive impact on the planet.
Purpose of the role:
The role sits within the department of Modelling and Digitalisation, a team of highly skilled modelling engineers, data scientists, and data engineers. The department specialises in multi-domain computational modelling, specialist data analysis, and the development of bespoke data products and cloud data platform solutions.
The role is focused on cell technology research and development and includes multi-domain modelling of our cell technology. You will work with a cross-disciplinary team of scientists and engineers to understand, improve, and innovate on Ceres’ cutting-edge cell technology.
Key responsibilities include leadership of cell modelling work packages, development of Ceres’ cell modelling techniques, collaboration across internal and customer-facing projects to solve challenging problems, and support for intellectual property creation. You will also be responsible for ensuring that your models and insights are utilized across our full chain of modelling and digital tools within the department and the wider company.
Knowledge and skills required for the role:
- Degree qualified in a STEM discipline, to a Bachelor, Master, or PhD level (e.g. Mechanical-, Automotive-, Aerospace-, Chemical & Process Engineering)
- Several years of experience in theoretical, computational, or experimental work in batteries and/or fuel cells, or other electrochemical devices
- Experience and willingness to learn about computational modelling in tools such as Comsol, Ansys, and Simscape
- Experience in machine learning and surrogate modelling techniques to accelerate modelling workflows is beneficial
- Ability to extract insight from complex data using tools such as Matlab or Python
- Deep understanding of analytical design and verification methods, and limitations of computational models