High-Throughput Development of High-Performance Copper Alloys via Additive Manufacturing

About the Project

PhD Opportunity: High-Throughput Development of High-Performance Copper Alloys via Additive Manufacturing

Institution: Heriot-Watt University, Edinburgh, UK

Supervisor: Dr. Faezeh Shalchy

Industry Partner: Aurubis, a global leader in copper production and multi-metal recycling.

Industry Supervisor: Dr. Owais Waseem

We invite applications for a fully funded PhD studentship for UK students only focused on accelerating the development of next-generation copper alloys through additive manufacturing (AM) and machine learning (ML).

About the Project

Copper alloys play a vital role in applications requiring high thermal/electrical conductivity, corrosion resistance, and mechanical strength. However, conventional alloy development is slow and resource-intensive. This PhD will pioneer a new approach by using metal 3D printing as a high-throughput experimental platform to rapidly synthesize and test novel copper alloys.

Key features of the project include:

• Designing and fabricating new copper-based alloys via AM with enhanced mechanical, electrical, and thermal properties.
• Exploring composition–structure–property relationships using advanced microscale characterization.
• Integrating machine learning models to predict and optimize alloy performance.
• Scaling up the most promising alloys for industrial validation (wire drawing and component manufacture).

The project is conducted in close collaboration with Aurubis, ensuring strong industrial relevance and opportunities for real-world impact.

Candidate Profile

We are seeking highly motivated candidates with:

• A background in Materials Science, Metallurgy, Mechanical Engineering, or related disciplines.
• Experience in experimental materials processing, additive manufacturing, or alloy characterization.
• Strong analytical and problem-solving skills.
• Interest in combining experimental research with computational or data-driven methods.

What We Offer

• A fully funded PhD studentship for UK based students (tuition + stipend).
• Access to state-of-the-art AM facilities, advanced microscopy, and characterization laboratories.
• Industrial collaboration and potential placement opportunities.
• Training in machine learning applications for materials science.

How to Apply

Please send a CV, cover letter, and academic transcripts to f.shalchy@hw.ac.uk. In your cover letter, explain your motivation for applying and how your background aligns with the project.

For any questions, feel free to reach out to f.shalchy@hw.ac.uk and/or o.waseem@aurubis.com.

Application is open until the position is filled.