Studentships

Constellium, a global leader in aluminium manufacturing and innovation, seeks to advance its capabilities by placing greater emphasis on thermo-mechanical process optimization and precipitate kinetics engineering. The design and optimization of aluminium alloys have traditionally relied on compositional tuning – adding or adjusting alloying. This requires tight compositional control hard to ensure, especially, with high-scrap content. This Ph.D. proposal aims to develop a comprehensive framework that integrates kinetic modelling and optimized thermal strategies to revolutionize aluminium alloy development – moving from a composition-centric approach to a thermal process-driven methodology. Objectives Critically evaluate the limitations of conventional alloy development routes based on alloying element variation. Support and validate previous findings and experiments. Implement advanced kinetic models to predict Thermo-Mechanical Ageing (TMA) condition for specific desired properties of high-scrap aluminium alloys. Design and validate tailored thermal treatment paths (Solutionising, quenching, ageing and interrupted ageing, etc.) Establish processing-microstructure-property relationships using experimental data and supported by modelling predictions Develop a digital decision-support tool to guide the UTC team doing proper heat treatment schedules based on kinetics predictions and desired mechanical property targets.   Expected results and Impact: This Ph.D. project is expected to develop high-scrap-content alloys and enhance digital, AI-integrated recycling by optimising process windows and thermal paths instead of focusing solely on chemical composition. Once specific mechanical properties, like yield strength and elongation, are identified for an application, a digital tool, for example, will recommend the suitable high-scrap alloy, its thermo-mechanical treatments, CO2 emissions, and energy consumption. By shifting the emphasis from "chemical control" to "kinetics and thermal process control," we seek to redefine high-performance, scrap-tolerant aluminium alloy design. This will help reduce environmental impact and energy costs.

Microplastics (MPs; plastic particles <5 mm) act as "Trojan horses" for micropollutants, concentrating antibiotics and facilitating their transfer through aquatic food-webs. While antibiotic adsorption to polymer surfaces is recognised, little is understood about how microbial processing alters these interactions and influences environmental persistence and antimicrobial resistance (AMR) risk. Aquatic sediments contain substantial loads of both antibiotics and MPs. Protists (single-celled eukaryotes) ingest MPs alongside bacterial prey despite their lack of nutritional value. Following ingestion, many protists egest particles as faecal pellets, repackaging MPs into aggregates with altered size and surface chemistry. We hypothesise that this biological conditioning modifies antibiotic adsorption-desorption dynamics, changing pollutant bioavailability, trophic transfer, and downstream AMR selection pressure. This interdisciplinary PhD will combine microbial ecology, molecular-modelling, and AI-enabled interaction analysis to elucidate how antibiotic–polymer binding is modulated within microbial food-webs. The project will adopt a focused three-fold approach: Quantify antibiotic–polymer binding energetics using molecular-modelling to identify structural determinants governing adsorption and persistence Measure adsorption–desorption behaviour under environmentally relevant laboratory conditions. Compare antibiotic binding before and after protist ingestion to test whether microbial processing mitigates or amplifies antibiotic carriage. In collaboration with AI-driven drug discovery company DeepMirror, we will co-adapt molecular representation-learning tools, previously applied to antimicrobial and global health challenges, to interrogate antibiotic-polymer interaction landscapes. AI-derived descriptors will guide experimental prioritisation and refine mechanistic hypotheses, accelerating insight while maintaining experimental validation. Background Information of the EngBio4Env Doctoral Focal Award (DFA) The first cohort of the EngBio4Env Doctoral Focal Award (DFA) is part of the UKRI TechExpert pilot programme. This provides a stipend of £31,805 per year for students who are eligible for Home fee status. As we have been allocated 16 enhanced studentships for the first cohort, our collective priority should be to recruit high-quality Home students and maximise uptake of this significant funding opportunity. While recruitment of international students remains possible within institutional and UKRI guidelines, we should focus our efforts on attracting talented Home applicants who can benefit from the enhanced stipend support available through the TechExpert programme. Key points of the UKRI TechExpert conditions: UKRI/EPSRC TechExpert Funding Pilot (2026 Cohort): The UK government, through UK Research and Innovation (UKRI) and the Engineering and Physical Sciences Research Council (EPSRC), has launched the TechExpert programme under the TechFirst initiative to strengthen the UK's research and innovation workforce in priority technology sectors Main features Provides a stipend enhancement of up to £10,000 per year for eligible doctoral students. Expected total stipend will be approximately £31,805 per year from the 2026/27 academic year. Funding is available for selected doctoral training investments aligned with the UK's Industrial Strategy and frontier technology sectors. This studentship starts 1 October 2026.  The programme is a pilot for the 2026 intake only, with funding currently planned for one cohort For Further information on the Doctoral Focal Award, please follow this webpage PhD Opportunities - EngBio4Env DFA