There’s no doubt that generative AI has become a permanent fixture in research and innovation.

Large Language Models (LLMs), such as Llama, GPT, and Mistral, are transforming how researchers discover, manage, and analyse information, enabling faster insights and accelerating breakthroughs.

Recognising the growing demand for AI skills, QCIF, through its partnership with the National Computational Infrastructure (NCI) and in collaboration with our newest capability, QCIF AI, has launched a new training workshop: Large Language Models (LLMs) for Research. 

This course has been designed to help researchers apply LLMs to streamline complex tasks and accelerate discovery through practical, reproducible workflows.

Delivered by Dr Moji Ghadimi, Head of QCIF Applied AI, the workshop equips participants with skills to apply these tools for literature review, data preparation, coding, analysis, and research writing, skills that are increasingly essential in today’s data-driven research environment.

Reflecting on the course, Dr Ghadimi explains:

“Researchers don’t need hype — they need practical, reliable workflows they can trust. In this workshop, I focus on showing exactly how LLMs can support core research tasks like literature review, coding, data preparation and summarisation, in ways that are reproducible, ethical, and grounded in real scientific practice.”

From theory to practice: Hands-on AI for research

The response to the workshop has been outstanding, with all spots quickly filled and participants praising its practical, research-focused approach.

One attendee remarked on its relevance, saying:

“This is quite a difficult subject to cover because of the rapid changes in the field, and the costs of running LLMs are also quite high. Moji has clearly put a lot of thought into applying these tools to research rather than everyday tasks.”

This interactive four-hour session goes beyond theory by providing hands-on experience with Python and Jupyter Notebooks. Participants learn how to automate the summarisation and organisation of scientific literature, build a simple Retrieval-Augmented Generation (RAG) workflow to answer research questions, generate and debug code using natural language prompts, and clean messy text data for structured analysis.

It’s this combination of theory and practical application, paired with participants’ curiosity to use AI ethically and effectively, that has made the course such a success.

Dr Ghadimi adds:

 “The enthusiasm from participants has been fantastic. It’s clear that researchers are eager not just to ‘use AI’, but to understand how to apply these tools safely, transparently, and in ways that genuinely accelerate discovery. That level of engagement is what motivates us to keep building these training programs.”

This workshop is part of a broader series on key topics in Machine Learning, Artificial Intelligence, and High-Performance Computing developed by QCIF in collaboration with the National Computational Infrastructure (NCI), as part of an initiative to raise awareness and build capability within the research community.

Established is 2024, the QCIF-NCI partnership has already trained thousands of researchers across Australia.

Dr Abdullah Shaikh, Manager Digital Skills Development at NCI, highlights the impact:

“It’s been our pleasure to have QCIF deliver foundational skills on machine learning and AI topics to our users. The NCI and QCIF training partnership has significantly enhanced our researchers’ capabilities using NCI’s services, particularly for our new and emerging users. QCIF’s approach to teaching and materials development, and its rapid adaptation to the evolving landscape of machine learning and LLMs, has been truly impressive.”

Interested in bringing an LLM-focused workshop to your organisation?

Due to high demand, QCIF is open to partnering with universities, industry and government organisations to deliver tailored sessions of this workshop. Content can be customised to meet your organisation’s specific needs and objectives.

To learn more, you can also take a look at the workshop GitHub page, where you can access the course content. https://qcif-training.github.io/llm_workshop/00_workshop_guide.html 

Ready to discuss options? get in touch with us via our contact form for a conversation.