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Akshay Rao

Top university

1 year ago

Materials for grid-scale energy storage University of Cambridge in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

This is a fully-funded, four-year PhD studentship at the University of Cambridge, covering tuition and providing a stipend. The project is interdisciplinary and includes collaboration with industry and multiple university departments.

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Cambridge

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Keywords

Computer Science
Machine Learning
Chemistry
Materials Science
Mathematics
Energy Materials
Physics
Applied Mathematic
energy storage systems

About this position

Fully-funded PhD position: AI-Accelerated Discovery of Energy Materials

We’re looking for a PhD student at the University of Cambridge to help accelerate the discovery of materials for grid-scale energy storage – an important part of the global transition to renewable energy.

This interdisciplinary, four-year studentship (starting October 2025) will combine advanced machine learning methods with novel experimental datasets at the Cavendish Laboratory. The student will develop new computational approaches to identify and understand factors driving battery degradation, efficiency, and lifespan.

The project is jointly supervised by Akshay Rao (Physics), James Fergusson and myself (DAMTP), with additional collaboration from Chemistry, the spinout company illumion , and the broader AI-for-Science community in Cambridge. Students with strong backgrounds in physics, chemistry, materials science, applied mathematics, or related disciplines are particularly encouraged to apply.

Deadline: 10 May, 2025
Full details in the flyer attached.

If you know students who might be interested, please do share or circulate within your networks. Thank you!

Funding details

This is a fully-funded, four-year PhD studentship at the University of Cambridge, covering tuition and providing a stipend. The project is interdisciplinary and includes collaboration with industry and multiple university departments.

What's required

Applicants should have a strong background in physics, chemistry, materials science, applied mathematics, or related disciplines. No specific GPA or language test requirements are mentioned, but interdisciplinary skills and interest in machine learning and experimental datasets are preferred.

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Professors

Professor at University of Cambridge

University Name
Country flag

United Kingdom

Research Interests

Organic Chemistry

Polymer Chemistry

Chemistry

Computer Science

Applied Mathematic

Professor at University of Cambridge

University Name
Country flag

United Kingdom

Research Interests

Computer Science

Machine Learning

Energy Materials

Physics

Applied Mathematic

Assistant Professor at University of Cambridge

University Name
Country flag

United Kingdom

Research Interests

Artificial Intelligence

Machine Learning

Computer Science

Chemistry

Physics