AI and ML Competency Centre, Resources for Researchers

Licences and API Access

Departments and colleges across the University of Oxford can now obtain access via IT services to two major generative AI tools: ChatGPT Edu and Copilot for Microsoft 365. These tools empower staff to use the capabilities of generative AI for research, teaching, and administration, all while ensuring data security and seamless collaboration within the University. See our purchasing page for more details or to purchase licences.

OpenAI API Access: While we are exploring options to offer OpenAI API access via the Edu Workspace, this is not currently available. However, we offer limited capacity for initial exploration of the OpenAI API. For more details, visit our FAQ section.

Coding Assistants: Accelerate your coding with tools like GitHub Copilot, which is free for academic staff and University students. These tools can help streamline coding tasks and improve productivity. Learn more about coding assistants and how to access GitHub Copilot on our FAQ page.

If you’re interested in other AI tools or APIs, we can provide advice and support with obtaining licences. Don’t hesitate to reach out to us for assistance via the expression of interest form.

Training Resources

Whether you’re new to generative AI or looking to scale your experiments, we offer a variety of training opportunities and resources tailored to researchers at the University of Oxford.

Basic Training to Use LLMs

Start with our foundational training sessions designed to help you understand and effectively use large language models (LLMs). These sessions are ideal for beginners and cover the basics of LLM capabilities and applications. View our basic training offerings on our Training page.

Custom Workshops for Researchers, Students, and Tutors

We have experience delivering tailored workshops for students and tutors in colleges and departments, covering topics like effective and responsible use of AI tools and discussions around academic integrity. We’re also happy to adapt these sessions for researchers, incorporating space for discussions on academic integrity, ethics, or other topics relevant to your work. Contact us to arrange a session or discuss your specific needs in our expression of interest form.

Scaling LLM Experiments

Interested in taking your LLM experiments to the next level? We are planning to set up workshops on advanced topics, such as scaling experiments with API access, agent frameworks, and robust methodologies for research. If you’d like to participate or provide input on these sessions, please get in touch via our expression of interest form.

OxRSE Training Resources

The Oxford Research Software Engineering (OxRSE) team offers a range of training resources, with plans to expand their offerings to include ML-specific courses. Stay updated on their training programs on the OxRSE Training page.

Cloud Computing for Research Competency Centre Courses

Get started with cloud resources through courses offered by the Cloud Computing for Research Competency Centre. These sessions are particularly relevant for researchers planning to use cloud platforms for machine learning projects. Find more information on the Competency Centre and their training options on the Cloud Computing for Research page.

Project Support We Offer

AI has the potential to transform research across a wide range of disciplines. We are here to support researchers at every stage, whether you're exploring initial ideas or implementing advanced solutions. Below are just a few ways AI can make an impact in research:

Data Analysis and Pattern Recognition

AI excels at processing large volumes of structured or unstructured data, uncovering patterns and insights that might otherwise go unnoticed. This is particularly valuable in data-intensive fields like genomics, social sciences, and climate research.

Predictive Modelling and Forecasting

Machine learning (ML) models can predict outcomes or trends based on historical data, making it a powerful tool in fields such as economics, epidemiology, and environmental science. These models can inform decision-making, guide experimental design, and forecast future trends.

Natural Language Processing (NLP)

NLP tools can analyse and interpret textual data, supporting disciplines like history, law, and literature. Tasks such as document summarization, translation, sentiment analysis, and information extraction from complex texts can be streamlined with AI.

Image and Video Analysis

AI-powered tools can analyse visual data, from medical imaging and satellite photography to historical artifacts and environmental monitoring. This is especially useful in fields like medicine, archaeology, and ecology.

How We Can Help You Along the Way

We understand that starting with AI in research can be daunting. Here are some ways we can support you:

Exploring AI for Your Work: If you're curious about how LLMs or AI might support your research but aren't sure where to begin, check out our workshops or reach out to discuss a custom session tailored to your needs.
Starting from an Idea: Have a few ideas for using AI in your research but don't know where to start? Get in touch! We can discuss your goals and point you toward helpful resources.
Understanding ML in Your Field: Found an exciting paper in your field that uses ML, but struggling with the technical details? We'd be happy to help explain the techniques or recommend learning resources to bridge the gap.
Building on Existing Work: Have a research idea inspired by an ML-based paper but unsure how to implement it? Our Research Software Engineers can support your team with ML implementations and recommend or provide training as needed.
Uncertain About AI's Role in Your Research? Not sure if your question fits into these categories? Let’s have a quick chat to explore your ideas and find the best way forward.

We’re here to help you use AI for impactful research—whatever your starting point. Reach out to us through our expression of interest form.

Other networks that might be of interest

Oxford and its wider community host a variety of programs and networks that explore the transformative potential of AI in research and education. Below, we highlight some initiatives that may be of interest to researchers. This list is not exhaustive, and we’re happy to include additional programs—please get in touch if you’d like to recommend one.

Schmidt AI Program

The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program at Oxford is part of an international initiative to enhance the use of AI in STEM fields. This program offers up to 55 postdoctoral fellowships over six years, providing researchers with the tools and training to apply AI techniques to disciplines such as engineering and the natural and mathematical sciences. Fellows gain access to mentoring, cohort learning, and opportunities to pursue independent research.

Reuben College

Reuben College emphasizes the interdisciplinary applications of AI and machine learning in areas such as clinical decision-making, medical imaging, and climate modeling. The College fosters collaboration through symposia, workshops, and seminars, promoting engagement with ethical and social implications of AI.

Oxford XML

Hosted by Wolfson College, OxfordXML is a cross-disciplinary machine learning community promoting collaboration across fields like physics, healthcare, and finance. It provides a platform for researchers to share knowledge through hybrid talks and workshops, exploring the transformative impact of ML.

Visual Geometry Group (VGG)

The Visual Geometry Group at Oxford conducts cutting-edge research in areas such as sign language recognition, self-supervised learning, audio-visual learning, and medical imaging. Their projects explore applications from sign language video analysis to visual-piano transcription and beyond. VGG’s work bridges fundamental AI development and applied innovations across diverse fields.

Oxford AI Society (OxAI)

The Oxford AI Society (OxAI) is a student-led organization dedicated to advancing interdisciplinary AI education and innovation. Through workshops, events, and global collaborations, OxAI supports learning, networking, and AI project development while emphasizing diversity and societal impact.

AI at Oxford

The University of Oxford’s “AI at Oxford” initiative highlights the University’s interdisciplinary research and resources in AI. It showcases collaborations across departments and industry, addressing ethical considerations and offering educational opportunities for researchers and students.

Bodleian Library: AI Guidance for Students

The Bodleian Library provides resources to help students use generative AI tools ethically and effectively in their studies. These include practical tips for academic tasks like reading, writing, and presentations while emphasizing critical thinking and academic integrity.