eResearch Analysts

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eResearch Analysts

The heart of the Skills Development group is our team of eResearch Analysts — research support professionals embedded within our Member institutions. 

Our eResearch Analyst team has a wealth of experience in data-intensive research and research computing support. All are dedicated to helping our Members’ staff and students make the best use of technology to improve their research outcomes. 

The eResearch Analysts provide mentoring, coaching and training to researchers from their host institutions. They each have a broad range of skills to achieve this, along with the capability to call on the knowledge of the whole Skills Development team and the rest of QCIF when this can deliver a better outcome for the researcher.

QCIF’s eResearch Analysts work alongside institutional colleagues in research computing, libraries and IT. In this way, they are fully informed to advise researchers on the most appropriate resources available, be they within their host institution, through QCIF, or through national schemes. 


“It was fantastic to receive support from knowledgeable analysts willing to enable innovative ideas and enhance user expertise.”

— Cesar Herrera Acosta, Coastal Ecology PhD student, JCU

“[The QCIF eResearch Analyst] saved us a lot of time and confusion, enabling us to get on with our research.”

— Bruen Smith, Mechatronic Research Engineer, USQ

Contact Us

Please contact your local eResearch Analyst for any questions about QCIF and to learn how they can support your research.

The University of Queensland

Dr David Green

ph +61 7 3346 6635

David is a QCIF eResearch Analyst and HPC Manager at The University of Queensland’s Research Computing Centre. He has long been using computers to “figure stuff out” and enjoys working with researchers to help them do the same. He was an academic in the Applied Physics and Computer Systems departments at the University of Technology, Sydney for almost 15 years. He has worked in research computing support roles at UQ since 2007.

Dr Marlies Hankel

ph +61 7 3346 3996
mob +61 4 0426 2445

Marlies is a QCIF eResearch Analyst and researcher. She has over ten years’ experience in high performance computing and cluster management. Her research interests include Quantum Dynamics and Computational Nanotechnology. Her main roles include looking after UQ’s HPC cluster users and QCIF’s partner share at the National Computational Infrastructure (NCI). If you are interested in obtaining computational time at the national compute facilities, please contact Marlies.

Queensland University of Technology

Craig Windell

ph +61 7 3138 6017

Craig is the QCIF eResearch Analyst at QUT. Craig is an IT professional with many years of experience at QUT assisting and supporting researchers to understand and use IT systems. He has performed a number of IT roles from desktop support, system administrating and system design. He has worked within QUT’s Faculty of Built Environment and Engineering, Institute of Health and Biomedical Innovation, ITS and more recently in cloud computing development and operations for the Visualisation and eResearch Group.

Griffith University

Amanda Miotto

ph +61 7 3735 4697

Amanda is the QCIF eResearch Analyst at Griffith University. She has worked at Griffith as an eResearch Support Specialist for the past nine years, initially as a bioinformatician, then as a software developer and technical resource on various projects, and more recently as an analyst for groups such as Compounds Australia and Innovations in Health Technology. Griffith researchers are welcome to ask Amanda for help in areas such as Python and R coding, high performance computing, scientific workflows, solution design or general data science questions.


Jason Bell

ph +61 7 4930 9229
mob +61 4 0963 0897

Jason is a QCIF eResearch Analyst at CQU. He provides high performance computing support and technical advice to CQU researchers. Jason’s research interests include video collaboration/conferencing tools, nonlinear optimisation, evolutionary algorithms, high performance computing, distributed and parallel computing, and robotics.

James Cook University

Dr Stefano Montanari

ph +61 7 4781 3199

Stefano is the QCIF eResearch Analyst at James Cook University. He is an eResearch Specialist at JCU’s eResearch Centre, with a particular interest in blockchain and decentralised ledgers. He completed his BSc, Honours and PhD in Marine Biology all at JCU, and was previously an aquarist at the university’s Division of Tropical Environments and Societies. Stefano will assist in the promotion and support of QCIF services to JCU researchers, including research computing, the technical side of data management, and digital skills training.

University of Southern Queensland

Dr Francis Gacenga

ph +61 7 3470 4560
mob +61 4 7707 2707

Francis is a QCIF eResearch Analyst and Manager (eResearch) at USQ. He is responsible for research computing service delivery, user support and training. He is an IT service management specialist with decades of experience working in government, industry and academia in computer programming, systems administration, teaching and research. Please contact Francis for research data management, storage and HPC access, support and training.

University of the Sunshine Coast

Dr Delaney Burnard


Delaney is the QCIF eResearch Analyst at USC. She assists in the promotion and support of QCIF services to USC researchers, including research computing and digital skills training. She is based at USC’s Sunshine Coast campus from Monday to Wednesday and works with researchers across all of USC’s campuses. She has a research background in molecular microbiology and bacterial genomics and did her PhD at USC. She has a broad skill set in high-performance computing from a researcher’s perspective, such as using Linux environments; experience in programming languages Python and Bash, including software installs and creating Bash scripts; and handling large genomic data sets. She also has experience in a variety of software platforms, such as Galaxy Australia for RNAseq analysis, SPSS for statistical analysis and Jupyter Notebooks for data science tasks.