PhD Opportunities in Optimisation in United Kingdom

The University of Nottingham is offering several fully funded PhD studentships for Home and International students through the EPSRC Doctoral Landscape Award. The studentships are based in Computer Science and begin on 1 October 2027. Applicants may propose an open research topic connected to one of the School’s research groups, including Cyber-physical Health and Assistive Robotics Technologies, Computational Optimisation and Learning Lab, Computer Vision Lab, Cyber Security, Functional Program...

PhD opportunity in the HyNOISE Doctoral Network: DC12, focused on building a systematic data assimilation model to predict thermoacoustic instabilities in hydrogen-fuelled combustion systems. The project is hosted by the University of Cambridge Engineering Department within a collaborative European network involving academic and industrial partners. The research aims to optimize the design of hydrogen-fuelled gas turbine injectors so that combustors are quieter and less susceptible to thermoacou...

PhD project at the University of Southampton on efficient optimization algorithms for large-scale interdiction problems on networks . This research focuses on how to protect vital transport, logistics, and communication networks against disruption. The project studies network interdiction , especially shortest-path interdiction , and may later extend to maximum-flow interdiction or uncertainty in disruption effects. You will work on mathematically sound algorithms, adaptive decomposition, sparse...

[Full award for UK students: home fees plus stipend. Course fees covered at the UK rate (at least £10,940 per year). Stipend is at least about £21,805 per year for the first year and for a further two and a half years.] PhD/D.Phil. studentship at the University of Oxford in Control Theory, Optimization and Learning , focused on data-driven control engineering for large-scale uncertain systems . This project sits at the intersection of control engineering, optimization, statistical learning, and ...

Applied and Computational Mathematics PhD at the University of Edinburgh (School of Mathematics, College of Science and Engineering). This research programme focuses on applied mathematics, computational mathematics, mathematical modelling, dynamical systems, numerical analysis, scientific computing, data science, machine learning, and AI. Research topics include fluid dynamics, climate and weather modelling, multiscale methods, molecular and statistical dynamics, plasma physics and fusion, math...

PhD project at the University of Southampton on AI-driven design of smart multifunctional metamaterials for next-generation aircraft . This research sits at the intersection of materials science , aerospace engineering , computer science , and physics . The project aims to design, optimise, and experimentally test lightweight metamaterial architectures that can absorb impacts, reduce cabin noise, and improve ultrasonic and thermal-wave imaging for hidden damage detection in aircraft structures. ...

PhD opportunity at the University of Southampton in freeform light routing in photonic circuits , supervised by Professor Marian Florescu in the Faculty of Engineering and Physical Sciences / School of Optoelectronics (ORC). This project focuses on integrated photonic circuits , optical interconnects , photonic crystals , and disordered photonics . The research aims to develop pathway-first design rules for low-loss, scalable optical routing around bends, junctions, and multi-port interconnects ...

[Full award for UK and overseas students: home or overseas tuition fees plus stipend. Stipend is at least the UKRI minimum for the first year and at least this amount for a further two and a half years.] Research area: This 3.5-year DPhil studentship at the University of Oxford focuses on integrated control architectures for next-generation synchrotron light sources. The project addresses a timely and technically rich challenge: modern synchrotron facilities rely on multiple interacting feedback...

PhD opportunity at the University of Southampton in deep equilibrium machine learning models for the efficient reconstruction of X-ray tomographic images . This project sits at the intersection of machine learning , computer vision , inverse problems , optimization , applied mathematics , and X-ray physics . The goal is to develop advanced AI tools that convert real X-ray measurement data into artefact-free 3D images, with a focus on realistic X-ray tomography (XCT) settings and large datasets. ...