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Research project support
Supporting data and compute intensive research
Supporting research in statistics, machine learning, natural language processing, geospatial analysis, Bayesian approaches, software engineering, data processing, modelling and simulation, bioinformatics and data management.
We provide advice and guidance, most of which is free of charge to University of Sydney researchers, research students, and affiliates. For extended support, please refer to our rate sheet.
Areas of expertise
Data science & AI
We have a team of data scientists, AI experts and software engineers to connect the best data science methods to your research problem.
Our team can provide support in data science, including solutions with:
- machine learning and probabilistic modelling
- data collection, transformation, analysis, and visualisation
- image & natural language processing
- software engineering
- automation
We deliver:
- short consultations and data transformation projects
- longer engineering and analysis projects in milestones of 2-12 weeks effort
- assistance with scoping and estimating work for grant proposals
- development of open-source software for data-driven research, with a focus on Python and R
- advanced training for researchers in data science technologies
Statistical consulting
We provide tailored statistical advice to University of Sydney researchers, research students, and affiliates.
Our team can provide:
- advice on experimental design
- support with data analysis and interpretation
- support with reviewing statistics in your project or grant application
- support with calculation of sample size and experimental power that will be needed in your grant application
We have a range of services available to support your research project, including access to global best practice bioinformatics pipelines, support with analyses and grant applications, training courses, and access to a researcher community.
Pipelines and analysis support
We develop global best practice data processing and bioinformatics pipelines and execute these for researchers on their datasets, at scale, on National HPC and cloud facilities. We engineer bioinformatics pipelines to maximise the efficiency and minimise run times and costs for HPC and Cloud facilities. You can find our public pipelines and analytical notebooks on Github and WorkflowHub.
We can assist with a range of bioinformatics data processing and analyses including:
- Short read and long read genomics and transcriptomics
- Metagenomics and metatranscriptomics
- Proteomics
- Single cell and spatial transcriptomics
- Multiomics integration
- Germline and somatic genome alignment and variant calling
- Genome and transcriptome de novo assemblies
- Differential expression
- Genome wide association studies
- Comparative genomics and phylogenetics
- Deep learning models for variant effect prediction and functional annotation
- Predictive modelling and biomarker discovery
We also assist with
- sensitive/protected and big data management lifecycles
- best practices and advise on the experimental design for next generation sequencing studies
- Data visualisation and quality control
- How to effectively use the University’s Research Data Storage systems for large datasets
- Specialist software and online platforms including QIAGEN’s CLC Genomics Workbench. Ingenuity Pathway Analysis and Galaxy Australia
- Popular open-source software
Grant support
We assist with:
- developing budgets and draft University in-kind contribution estimates for computing, data storage, and data analysis services for grant applications.
- preparing and reviewing project proposals for computing resources grants, including the National Computational Merit Allocation Scheme, Intersect HPC Allocation Scheme, Microsoft Azure and AWS Cloud Research grants.
Training courses
We deliver a range of bioinformatics training courses as a part of the National Bioinformatics Training Cooperative. Our events are open to all University of Sydney research staff, students and affiliates.
Modelling, simulation and visualisation
Access assistance with modelling, simulation, scientific visualisation and informatics.
Our team can assist with:
- data-intensive and computationally-intensive modelling, simulation, visualisation, and informatics executed on National HPC facilities, and Argus VRDs, and Commercial Cloud. This includes support for accelerating, parallelising and scaling up algorithms, developing portable and reusable code, workflow management and automation, optimising code for, and transitioning code between HPC and Cloud services.
- analyses – including computational chemistry, molecular dynamics, computational fluid dynamics, finite element analyses, mathematical modelling, machine learning, computer vision, image analyses, scientific visualisation, GPU programming.
- preparing and reviewing project proposals for computing resources grants, such as the National Computational Merit Allocation Scheme, Intersect HPC Allocation Scheme, and Commercial Cloud research grants. We assist with resource benchmarking and demonstrating code scalability as required by these schemes.