QLD Cyber Infrastructure Foundation (QICF) Placement Opportunities

QCIF is a not-for-profit company dedicated to providing high-performance computing, data storage, and other cyber infrastructure services to support research and innovation in Queensland.

QCIF’s purpose is to enhance research capabilities and outcomes by providing researchers with access to advanced computing infrastructure and resources. They offer a wide range of services and resources, including high-performance and cloud computing, data science and bioinformatics analysis, research data management tools, digital skills training, and software support.

QCIF, in with partnership with UQ Graduate School, is providing opportunities to PhD candidates to develop their research and transferable skills through a HDR placement. HDR candidates in the EAIT Faculty, or those with a data research background are particularly invited to apply.

Intended start date: flexible (depending on the project)

Total days: 60 working days (5 days a week or part-time depending on the right candidate)

Location: QCIF office- UQ St Lucia Campus

Please apply using the "APPLY" button below (please do not submit a my.UQ request for this placement). We will then contact shortlisted students to organise interviews with the host supervisor.

This placement is unpaid but you might be eligible to apply for one of the Graduate School Scholarships

Apply

Please see list of immediately available  projects below  Further projects may become available as QCIF examines proposals to develop other resources that servicewould service their members and customers.

Quality Systems Implementation Support

Project summary:

In support of QCIF’s ambition to achieve ISO 27001 accreditation, we are looking to undertake a project to review and document existing processes, develop a gap analysis of missing requirements, and to build policies and procedures to address those gaps. We are looking for someone with a thorough understanding of business processes in the computer science and technology space and an interest in quality systems.

Desired outcomes:

Provide a written report on existing processes and their place within a quality management framework
Provide a written gap analysis on additional processes which need to be developed/implemented to meet requirements of ISO accreditation
Optional/time dependant: preparation of policies and procedures to address some or all of the identified gaps.

Project lead: Lachan Hoole

Creating a Research Training Module in Natural Language Processing

Project summary:

Natural Language Processing is a machine learning technology which allows computers to process human language to accurately extract meaning and sentiment. This capability means that NLP has tremendous potential applications in virtually all fields of research, but as an emerging technology, it is still a tool which few researchers have the expertise to use. This project will develop a practical training workshop to provide researchers with the skills to start using NLP in generating and analysing their research data. The workshop will be developed in the style of The Carpentries training material, to enable QCIF’s team of digital skills trainers to deliver half- or one-day hands-on courses to researchers at QCIF member universities.

Desired outcomes:

Review of existing open-source NLP training material and evaluation of its applicability to the QCIF training format.
Preparation of a workshop outline, including core topics, background information, worked examples, and sample datasets.
Production of a full NLP training manual in the markdown style of The Carpentries.

Project lead: Dr Mark Crowe

Conducting Network Meta-Analysis in R with Outputs and Plots Comparable to Stata’s NMA Packages

Project summary:

The STATA “mvmeta” package is used extensively to conduct NMA to synthesize direct and indirect evidence from a network of trials. The plots generated for visualization of results enhance the understanding of the outputs. Many data scientists now use R in preference to STATA, and this project aims to explore and develop a resource from existing R libraries to generate numerical summaries and graphical tools comparable to STATA routines.

Desired outcomes:

Identification of relevant R libraries to provide functionality comparable to mvmeta
Documentation on the use of those libraries to produce the desired summaries and graphical outputs and illustration of application using example datasets
[Likely] Development of software packages and analysis pipelines to streamline the generation of STATA-comparable outputs from R

Project lead: Dr Farah Zahir

Developing a Tutorial to Demonstrate Statistical Techniques for Undertaking Non-Inferiority and Equivalence Trials.

Project summary:

When evaluating new clinical treatments, randomized controlled trials were traditionally designed to show superiority of one treatment over the other. Recently however, treatments are being developed which may not be better than existing treatments clinically but are more cost effective or less harmful. In these cases, demonstrating superiority is not of interest, but the aim is to confirm that the new treatment is not worse (non-inferiority), or equal (equivalence) to the existing regimen. Traditional statistical methods to demonstrate the differences are not easily applied to show equivalence or non-inferiority. This project is to develop a resource for design and reporting of non-inferiority and equivalence trials in R.

Desired outcomes:

Literature search to show design of such trials.
Development of a tutorial using R and RStudio to show statistical techniques for conducing non-inferiority and equivalence trials alongside practical implications and interpretation of results.
Illustrations using existing datasets.

Project lead: Dr Farah Zahir

Capacity-Scoping for Disaster Management Response Data Analysis Capabilities

Project summary:

Over the past few years, bushfires, floods, and COVID-19 have exposed shortcomings in the capacity of disaster response management specialists to deal with large quantities of diverse and unstructured data. Several QCIF member universities have disaster management research groups, while QCIF has expertise in data science and software development; coordinating these groups could provide rapid surge capacity to support specialists in a particular field of expertise in the event of an emergency. This project would review the capacity of QCIF and university research groups to provide such support, and develop a model for engagement with relevant government agencies.

Desired outcomes:

Report on the range of research being carried out by researchers at QCIF member universities into disaster management, including a skills and capacity audit
Business/engagement plan for the QCIF data science team to coordinate involvement of this network of data analysts to support disaster response management in the event of a state or national emergency.

Project lead: Justin Scott

ReDBox - Project Blacklight Integration

Project Summary:

ReDBox offers seamless integration with discovery portals to facilitate the publication of metadata for research datasets. While the existing integration options primarily cater to cloud and subscription-based platforms, we aim to address this by introducing Project Blacklight – an open-source, lightweight discovery portal solution. This project seeks to establish and configure a Project Blacklight installation tailored to institutions lacking a discovery portal. Our objective is to integrate this installation with ReDBox, enabling the seamless display and accessibility of published datasets through Project Blacklight. With this initiative, we aim to enhance research data discovery and accessibility for a wider range of institutions.

Desired Outcomes:

1) Aid in the design of the Project Blacklight instance including layout and schema requirements

2) Implement and configure a Project Blacklight instance that can be used for publishing datasets

3) Enhance ReDBox to be able to provide the data publication metadata it stores to the Project Blacklight instance

4) Implement scripts to support the configuration and deployment of the applications

5) Produce supporting documentation to configure and deploy the applications

ReDBox Self-Service Form Configuration

Project Summary:

ReDBox offers institutions the flexibility to customize metadata management forms, enabling them to adhere to their institution's specific policy requirements. At present, these forms' layout is defined using JSON structures stored in a Mongo Database and is typically customized by developers. The objective of this project is to enhance the user experience by developing intuitive screens within the web interface. These screens will empower authorized users to easily modify the form configurations, eliminating the need for developer intervention. By enabling user-friendly customization capabilities, this project aims to streamline the process of adapting form layouts to meet institutional policy requirements, fostering greater autonomy and efficiency for researchers.

Desired Outcomes:

1) Assist in the production of the screen designs for the self-service form configuration

2) Implement the screens inside the ReDBox platform

3) Produce supporting documentation around its configuration and use

Devops in Microsoft Azure Cloud

Project Summary:

The Software Solutions team specializes in providing managed services for their software platforms, catering to customers who utilize diverse cloud platforms like AWS, OpenStack, and Google Cloud. To ensure consistent management across these platforms, the team has implemented DevOps processes leveraging industry-standard tools such as Terraform, Packer, and Ansible. The objective of this project is to expand our existing managed services offering to include support for Microsoft Azure Cloud.

Desired Outcomes:

1) Analyse the current processes with existing cloud platforms to develop a plan to implement Azure Cloud Support

2) Implement packer configuration to build images in Azure Cloud

3) Develop terraform templates to provision the infrastructure in Azure Cloud

4) Deploy a proof of concept ReDBox instance in Azure Cloud

Software package / user interface development for KeyPoint, a secure platform for collaborative analysis of sensitive research data

Project background:

KeyPoint is an eResearch platform developed by QCIF that enables data custodians to manage and share sensitive research data with approved researchers in a scalable, fully governed, and highly secure environment. KeyPoint is designed to support a wide range of use cases, with individual software development and user-interface projects required to implement each package.

N.B. Multiple placements are available for this project, each addressing one or more of the desired outcomes.

Desired outcomes:

Enhanced/expanded functionality added to KeyPoint that supports particular use cases, for example:
- Multi-faceted approval process for data ingress or data egress from the platform
- Support for federated learning use cases
- Import of ingressed data into a database
- Build out of KeyPoint’s forensics capability

Preparation for ISO/IEC 27001 self-assessment and/or certification
- Remediation work from external penetration testing
- Gap analysis for processes and procedures
- Document implemented controls
- Design/develop missing controls, processes, and procedures

Governance alignment to Member-specific governance policies

Building Integrated Functionality to Enhance Usability of the Nectar Research Cloud

Project background:

QCIF operates the Queensland node of the Nectar Research Cloud, a national platform providing extensive and powerful computing resources to Australian researchers. The Nectar Research Cloud incorporates cutting-edge computational infrastructure and new features are continually being added. This project will focus on building systems to further integrate services for improved usability and functionality.

Desired outcomes:

Prototyping of possible solutions for researchers and research communities that leverage and combine the underlying capabilities of the research cloud to deliver new services, e.g.
1. Determine how national projects could burst to the reservation system for specialised compute:

i. Galaxy Australia

ii. EcoCommons

iii. TERN

1. Boost a virtual desktop to a specialised compute
2. Determine how national projects could use virtual desktop service or Jupyter service rather than having to do it themselves.