Artificial Intelligence Jobs

• Norwich
• £20,409 pa
• Entry level
• Contract

Develops hybrid fault diagnosis methods for offshore wind turbine drivetrains, combining physics-based analytical models with AI-driven data analysis to improve fault detection and reduce false alarms. The work spans numerical simulation, finite element modelling and experimental validation, with the goal of supporting predictive maintenance and cutting downtime costs.

Accelerometers

• Norwich
• Entry level
• Contract

Develops hybrid fault diagnosis methods for wind turbine drivetrains, combining analytical models of drivetrain physics with AI-driven data analysis to improve fault detection and classification. Work spans analytical studies, computer simulations, finite element analysis, and experimental development and validation, addressing a gap in condition monitoring for electrical faults.

• Nottingham
• Hybrid
• £21,805 pa
• Entry level
• Contract

A fully funded four-year PhD developing thermodynamic and transient models of hybrid energy systems combining gas turbines, carbon capture, biomass gasification and solar thermal. The work covers techno-economic and life cycle assessment plus AI-driven optimisation and control, with a three-month industrial or policy placement through the Net2Zero CDT.

MATLAB · Python · Aspen Plus +2

• Guildford
• £21,805 pa
• Entry level
• Permanent

Develops a computational framework combining computer vision, graphics and machine learning to speed up and improve cinematic camera lens design and simulation. The work covers forward simulation of candidate lens configurations and inverse design of lens architectures against imaging or perceptual objectives, using differentiable rendering and data-driven models. Based at the Vision, Speech and Signal Processing group under Dr Marco Volino and Dr Jean-Yves Guillemaut, with close industry collaboration.

PyTorch · TensorFlow

• Exeter
• £21,805 pa
• Contract

Investigates how two neuroscience developments—astrocyte-neuron interactions and spontaneous retinal waves—can improve deep networks. The work involves adding astrocyte-inspired regularisation to training and using synaptic plasticity rules for network initialisation, then testing generalisation, robustness, explainability, learning speed and data efficiency.

• London
• £18,000 pa
• Entry level
• Contract

Develops an AI-enabled decision-support framework combining building-performance simulation, machine learning, GIS and remote sensing to optimise green roofs and façades for energy, carbon and thermal performance. Primarily computational, with no routine lab or fieldwork, and scope refined with the successful candidate.

GIS

• Exeter
• £21,805 pa
• Entry level
• Contract

Develops and evaluates AI, machine learning and deep learning methods for grading retinal fundus images to detect diabetic retinopathy, glaucoma, cataract and AMD. Works with large datasets including EyePACS, UK Biobank and NHS sources, comparing algorithm accuracy against NHS clinicians and optimising explainable models for clinical trust.

OCTA · CCM · OCT

• Birmingham
• On-site
• £21,805 pa
• Entry level
• Contract

Develops a physics-informed AI framework to design and optimise alternative cooling mechanisms and refrigeration cycles, integrating thermodynamic modelling, machine learning and multi-objective optimisation. Experimental work validates selected combinations, with scope to balance computational and lab effort. Based in the School of Chemical Engineering alongside sustainable cooling and energy storage research centres.

• Oxford
• £21,805 pa
• Entry level
• Contract

Investigates how the rapid growth of AI can be supported by more sustainable, circular hardware and infrastructure, linking computational performance to the physical materials and equipment required. Develops scenarios for UK AI and data centre growth, mapping hardware requirements to critical raw materials and modelling how lifetime extension, reuse, repair and remanufacture could cut environmental impacts. Based in the Circular Economy and Sustainability Lab, contributing to the Circular Electricals and Electronics Project.

Data Centres

• Coventry
• On-site
• £21,805 pa
• Entry level
• Contract

Develops medium-voltage solid-state transformer cells for hyperscale AI data centres and net-zero grids, tackling high-frequency power conversion, compact magnetic links and electrical-thermal degradation under high-dv/dt stress. Combines multi-physics finite-element modelling in ANSYS/COMSOL with experimental validation in a high-voltage power electronics lab, culminating in a scaled hardware prototype.

ANSYS · COMSOL · Solid-State Transformers +2

• Cranfield
• £21,805 pa
• Entry level
• Contract

A PhD studentship researching AI-on-RAN, optimising distributed and mobile inference of large language models by adapting token, memory and bandwidth use in real time. The work spans AI and telecoms, with cross-university FTH training and exposure to defence, government and infrastructure stakeholders, aiming to shape 6G network design.

AI-on-RAN · 6G

• London
• £23,805 pa
• Entry level
• Contract

Develop a framework combining a differentiable reacting flow solver with a machine learning-based controller to anticipate and mitigate extreme events such as flashback and thermoacoustic instabilities in hydrogen and SAF combustion. The role sits within the European CONTEXT project, using high-fidelity simulations and Imperial's HPC facilities, with applications spanning novel actuators like spray water injection and electrically-driven droplet control.

HPC

• Barcelona, Spain
• Hybrid
• Entry level
• Internship

PhD research internship tackling open problems in spatial perception and localisation within the Spatial Intelligence Team. You survey and prototype state-of-the-art methods for scene matching, SLAM/VIO and 3D reconstruction, benchmarking ideas against real-world data and compute constraints, and report findings to a Europe-distributed team.

PyTorch · NeRF · Gaussian Splatting

• Manchester
• £21,805 pa
• Entry level
• Contract

A 3.5-year PhD developing an AI-enabled digital twin framework to support circular retrofit decision-making in ageing public buildings such as schools and healthcare facilities. The research integrates building condition data, asset records, material inventories and lifecycle information to evaluate component condition, estimate remaining service potential and prioritise reuse over replacement, validated through public-building case studies.

• London
• Hybrid · 1 day in office
• £46,000 – £52,000 pa
• Contract

Join a national security team building robust AI agents and realistic training environments to defend critical infrastructure from cyber threats. Day-to-day work spans realistic network simulation environments, novel agent architectures, and evaluation tasks, requiring strong Python, Linux and git skills plus a research mindset. Hybrid role with just one day per week in the central London office.

Python · Git · Linux