The Data Science CRP provides essential expertise in bioinformatics, statistics, biometry, and applied AI, enabling Higher Degree by Research (HDR) students and researchers to harness the full potential of their data.
We support the entire research lifecycle, from initial data collection and management to advanced analysis and visualisation.
Services include access to Subject Matter Experts at salary cost for on-demand support or embedded personnel, collaboration on grant applications, upskilling HDRs and ECRs through training workshops and co-supervision, and ensuring researchers can work effectively with sensitive data.
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Research Support
Researchers and Higher Degree Research students can receive a free consultation to help with research projects, publications and upcoming grant applications.

UQ TRE
UQ Trusted Research Environment (TRE) enables researchers to work and/or share sensitive data while ensuring data sovereignty, security, and privacy. We offer guidance on data access applications, data management and data governance for sensitive data.

CHQ Statistical Support
Request support from CHQ statistical support service
Leadership Team
Head of Statistics
Life Science and Health Team
Senior Biostatistician and Bioinformatician
Agriculture and the Environment Team

Research Fellow/Senior Research officer
Digital Health Team

Dr Ronald Dendere

Vitaly Gnyubkin
BioCommons UQ
Dr Nigel Ward
A/Director: Platforms
Dr Melissa Burke
Training Manager
Dr Gareth Price
Project Lead - Galaxy Australia
Dr Igor Manukin
User Support - Galaxy Australia
Operations Team
Aria Liu
Data Science Training Support
Registration Opens Soon
Introduction to NGS and Bioinformatics Analysis
26 Feburary 2026 9:00am–12:30pm in Bioinformatics
Learn how to analyse Next-Generation Sequencing (NGS) data using the Galaxy platform, covering key bioinformatics workflows such as quality control, read alignment, and variant analysis in a beginner-friendly, code-free environment.
Introduction to SPSS
27 Feburary 2026 9:00am–5:00pm in Biostatistics
Learn how to import, manage, visualise, and conduct basic statistical analyses using SPSS.
Statistical Comparisons using R
12 March 2026 9:00am–5:00pm in Biostatistics
Learn how to choose, perform, and interpret statistical tests using R, including correlation, contingency tables, chi-square tests, t-tests, and ANOVA, with examples and exercises focused on biological and clinical research.
Statistical Comparisons using SPSS
20 March 2026 9:00am–5:00pm in Biostatistics
Learn how to select, perform, and interpret common statistical tests using SPSS, with a focus on applying inferential statistics to real-world research data.
Assembly of Long-Read Sequencing with Galaxy
26 March 2026 9:00am–12:30pm in Bioinformatics
Learn how to generate and assess high-quality bacterial genome assemblies by combining Oxford Nanopore and Illumina data using user-friendly tools on Galaxy.
Exploring and Predicting using Linear Regression in R
31 March 2026 9:00am–5:00pm in Biostatistics
Learn to apply and interpret linear regression in R through hands-on practice.
The Principles of Machine Learning
16 April 2026 9:00am–5:00pm in Biostatistics
This workshop provides the introduction to machine learning, guiding participants through core concepts, key algorithms, data preparation, and hands-on model building to support research-driven applications.
RNA-seq using Galaxy
23 April 2026 9:00am–5:00pm in Bioinformatics
This beginner-friendly workshop introduces RNA sequencing and its bioinformatics analysis using the Galaxy platform, guiding participants through key steps from raw data quality control to differential gene expression analysis
Exploring and Predicting using Linear Regression in SPSS
24 April 2026 9:00am–5:00pm in Biostatistics
Learn to explore, analyse, and interpret data relationships using linear regression techniques in SPSS through hands-on, practical sessions.
Easy automated image classification with Python and Roboflow
7 May 2026 9:00am–1:00pm in Biostatistics
General enquiries
- Email: datasciencecrp@uq.edu.au
- Phone: +61 7 3346 2624
HDR student enquiries