Artificial Intelligence Jobs

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts from industry and academia to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The intern also publishes optimisation techniques via developer blogs or conferences and helps influence next-generation hardware, software and programming models.

NVIDIA · Zürich, Switzerland

Research and develop techniques to GPU-accelerate deep learning, machine learning and other AI workloads, working with technical experts to analyse and optimise complex AI and HPC algorithms on modern CPU and GPU architectures. The role also involves publishing optimisation techniques via developer blogs or conferences and influencing next-generation hardware and software design.

University of Exeter · Exeter · £21,805 pa

Develops a resource-aware AI framework for 2D and 3D medical imaging that adapts computation to case complexity, clinical risk and available hardware. Investigates where unnecessary computation occurs, builds a configurable model family, and validates it on population-scale abdominal MRI (UK Biobank) and near-patient dermatology imaging, with safety assessed across patient subgroups.

Scale AI · London

New grad engineers own customer-facing work from day one, shipping products, speaking directly with customers and iterating quickly. The Global Public Sector team builds custom AI applications, training data pipelines for national LLMs, evaluation infrastructure, agentic AI tooling and fraud-detection systems, working in Python, TypeScript, React and MongoDB.

Scale AI · London

Interns own real, shipped work on the same roadmaps as full-time engineers, building agentic AI applications, evaluation infrastructure, data pipelines and fraud-detection systems for Scale's Global Public Sector team. Work spans Python, TypeScript, React and MongoDB, with mentorship and a strong ownership culture.

University of Exeter · Exeter · £21,805 pa

Develops explainable, trustworthy machine-learning models for early dementia detection, integrating multimodal data such as neuroimaging, cognitive assessments, genetics and biomarkers. Uses latent knowledge-enhanced representations, vision-language agentic frameworks and uncertainty quantification, with clinician evaluation of bias and fairness. Validated through a longitudinal multimodal prediction and explanation system.

University of Oxford · Oxford · £21,805 pa

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.

University of Oxford · Oxford · £39,424 – £47,779 pa

Develops novel statistical and machine learning methods for large-scale genomic, phenotypic and health data, covering areas such as genomic language models, multimodal and federated learning, and multi-ancestry methods. Builds scalable, reproducible research software applied to biobank-scale datasets, evaluates statistical and predictive performance, publishes findings and guides junior researchers in the Palamara Group.

University of East Anglia · Norwich · £21,805 pa

A PhD studentship developing multispectral and hyperspectral imaging combined with machine learning to detect and classify marine litter from aerial and drone-based platforms. The researcher will characterise litter material reflectance in the lab, curate imaging datasets, and build models robust to changing illumination and sensor differences, based in the Colour & Imaging Laboratory and working with CEFAS scientists.

Anonymous · Birmingham · £35,000 – £38,000 pa

Graduate role bridging business users and technical teams, investigating processes, analysing data and identifying where process change, automation or AI can improve efficiency. Involves process mapping, requirements gathering, system testing and supporting implementation of technology-led solutions, with mentoring and exposure to real transformation projects.

The Francis Crick Institute · London · £47,500 pa

Lead a computational project modelling how driver mutation clones interact with their microenvironment in chronic liver disease and liver cancer. Develop graph neural networks, transformers and generative AI on large-scale spatial transcriptomics, single-cell and imaging data, in a cross-institutional collaboration with the Wellcome Sanger Institute's Lotfollahi Lab.

University of Birmingham · Birmingham · £21,805 pa

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.

CrowdStrike · London

Internship on CrowdStrike's Technical Analysis Cell, researching nation-state and criminal intrusions through reverse engineering of malware and tooling. The intern documents findings, builds automation for malware analysis, creates host- and network-based detection signatures, and produces threat intelligence reporting for varied audiences.

CrowdStrike · Germany

Internship on CrowdStrike's Technical Analysis Cell, researching nation-state and criminal intrusions through reverse engineering of malware and developing automation tools for threat tracking. Involves creating host- and network-based signatures for large-scale hunting and producing finished threat intelligence reporting for customers.

Humanoid · London

Teleoperate humanoid robots and follow structured procedures to generate high-quality datasets for training AI models, using on-site tools such as the Universal Manipulator Interface. A large part of the work is annotating and labelling multimodal data with precision, escalating anomalies and suggesting workflow improvements. Full training is provided and no technical background is required.