Research PhD Student in Glasgow

Glasgow Engineering Futures Fellow in Structural Engineering

Title: Future steel connections integrating machine learning and optimised 3D-printed metals (FUSION)

The aim of this project is to produce a reliable and full characterisation of the mechanical behaviour of 3D-printed stainless steel, enabling its safe use in the design of sustainable and resilient steel and stainless steel hybrid structures.

The project complements current design needs for improving the resilience of steel structures through the strategic use of inherently durable and ductile materials at the joints. Additive manufacturing (3D printing) is transforming construction by enabling material‑efficient, optimised designs and automated fabrication. However, the characterisation of 3D-printed metals under complex loading conditions in structural applications remains a major challenge. International research on 3D-printed metals underscores a critical gap and an urgent need for standardised frameworks to enable their use in infrastructure applications.

This project addresses this gap by targeting structural‑scale applications with a focus on the most demanding components in steel frames: the connections. The research pioneers the integration of 3D-printed stainless steel into structural connections, combining advanced manufacturing, artificial intelligence, and topology optimisation.

Before this potential can be realised in practice, essential material and component data are missing. Accordingly, the PhD student will conduct testing at the University of Glasgow to ascertain the full stress‑strain response of 3D‑printed stainless steel for the first time. The research will deliver:

• Discovery of constitutive material laws through extensive testing and physics‑informed machine learning, including evaluation of steel connections at sub‑assembly level.
• Formulation and implementation of generalised constitutive and fracture models for 3D‑printed structural stainless steel within a finite element modelling framework.
• Topology optimisation of sub‑assemblies and full connections to minimise material usage while ensuring structural resilience.
• Experimental and numerical validation of optimised 3D‑printed stainless steel connection sub‑assemblies and full connections.

The PhD student will gain advanced skills in experimental, analytical, and numerical methods, with the opportunity to work within the environment of the Glasgow Computational Engineering Centre (GCEC) and Materials & Manufacturing Research Group (MMRG) at the University of Glasgow, and collaborate with external partners. The outcomes will contribute to establishing the foundations for future codification of 3D‑printed stainless steel in structural applications.

How to apply:To apply, please contact Dr Manuela Cabrera Duran Manuela.cabreraDuran@glasgow.ac.uk with:

• A short statement of motivation outlining your interest, academic background, and suitability.

An interview will be conducted for shortlisted applicants.

Funding Notes: Scholarship available covering tuition fees and stipend (£20,780 in the academic year of 2025/26, projected to raise annually with the inflation).

• A first class or upper second-class honours degree (or international equivalent) in Engineering, Mathematics, Statistics, or a related discipline.

Requirements:

• Strong background in structural engineering, materials, or mechanics.
• Excellent analytical, problem‑solving, and communication skills.
• Ability to work both independently and as part of a multidisciplinary research team.
• Desirable experience in one or more of the following: finite element modelling, experimental testing, machine learning or additive manufacturing would be an advantage.

Seniority level

Internship

Employment type

Full-time

Job function

Education and Training

Industries

Software Development