Dabo Guan
4 months ago
Fully Funded PhD in Securing Critical Material Supply Chains for Hydrogen Production at University College London University College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
This is a fully funded studentship covering tuition fees and a tax-free stipend for up to 4 years. Funding is provided under the EPSRC Doctoral Landscape Award and is available to both UK and international students.
Deadline
Expired
Country
United Kingdom
University
University College London

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About this position
A fully funded PhD position is available at University College London (UCL) to work on securing critical material supply chains for hydrogen production in the UK, under the EPSRC Doctoral Landscape Award. The project addresses the challenge of building resilient and secure supply chains for critical materials, such as platinum and nickel, which are essential for the net-zero hydrogen economy. The research will be based at UCL’s Bartlett School of Sustainable Construction, a leading centre in this field, and will be supervised by Professor Dabo Guan and Dr.
Jing Meng. The project combines data science, network analysis, and techno-economic analysis to map global supply networks, identify vulnerabilities, and design strategies for resilience, including recycling and strategic sourcing. Applicants should have a strong quantitative background (Engineering, Economics, Computer Science, or Physics), excellent analytical and problem-solving skills, and ideally programming experience in Python or R.
The studentship is fully funded for up to 4 years, covering tuition and a tax-free stipend, and is open to both UK and international students. For application details, candidates should refer to the UCL EPSRC DTP project catalogue and use the specified project ID.
Funding details
This is a fully funded studentship covering tuition fees and a tax-free stipend for up to 4 years. Funding is provided under the EPSRC Doctoral Landscape Award and is available to both UK and international students.
What's required
Applicants must have a First or 2:1 degree in a quantitative discipline such as Engineering, Economics, Computer Science, or Physics. Strong analytical and problem-solving skills are essential. Programming experience in Python or R is advantageous. The position is open to both UK and international applicants.
How to apply
Visit the provided project catalogue link for full details and application instructions. Use Project ID 2531bd1614 when applying. Prepare your application materials as specified on the UCL EPSRC DTP website.
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