School of Electrical Engineering and Computer Science Full-time (100%), fixed-term position for up to 2 years and 9 months Base salary will be in the range $80,448.78 - $107,104.10 17% Superannuation (Academic Level A) Based at our St Lucia Campus About This Opportunity We are seeking a strong candidate who will support the design and implementation of software, configuration scripts, and data processing workflows for ongoing research projects. Additionally, this role will involve data engineering tasks such as acquiring, processing, and managing health-related datasets, from research databases like MIMIC to real-world electronic medical records from platforms, such as Cerner and Epic. Beyond data engineering, the role includes aspects of data science, such as conducting data analysis, feature engineering, and building machine learning models for tasks like classification and regression Key responsibilities will include: Research and Technical Support: Collaborate with researchers and HDR students to identify data/software needs and support data-driven solutions, including research outputs. Develop and maintain full-stack applications for research workflows (e.g., Natural Language Processing (NLP), Information Retrieval (IR), Retrieval-Augmented Generation (RAG), and AI/ML-based systems). Build and manage data pipelines using open-source or cloud tools (e.g., Apache Airflow, AWS Managed Workflows, Google Cloud Compose). Create and maintain user interfaces and APIs for data access and interaction. Ensure data security, integrity, and compliance with governance and privacy requirements. Stay current with technologies in data engineering, cloud infrastructure, and software development to support ongoing research initiatives. Supervision and Researcher Development: Provide technical support and informal mentoring to HDR students and research project teams. Assist with data preparation, software setup, and infrastructure under senior staff guidance. Citizenship and Service: Foster a collaborative, inclusive team by sharing knowledge, maintaining documentation, and engaging in team activities. Support group operations through environment setup, tutorials, demos, and contributions to workshops or technical sessions. Demonstrate collegial behaviour and uphold UQ values in daily interactions and professional conduct. This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance . About UQ As part of the UQ community, you will have the opportunity to work alongside the brightest minds, who have joined us from all over the world, and within an environment where interdisciplinary collaborations are encouraged. At the core of our teaching remains our students, and their experience with us sets a foundation for success far beyond graduation. UQ has made a commitment to making education opportunities available for all Queenslanders, regardless of personal, financial, or geographical barriers. As part of our commitment to excellence in research and professional practice in academic contexts, we are proud to provide our staff with access to world-class facilities and equipment, grant writing support, greater research funding opportunities, and other forms of staff support and development. The greater benefits of joining the UQ community are broad: from being part of a Group of Eight university, to recognition of prior service with other Australian universities, up to 26 weeks of paid parental leave, 17.5% annual leave loading, flexible working arrangements including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process. About You Qualifications and training equivalent to an undergraduate degree in Computer Science, Data Engineering, Data Science, Health Informatics, or related field and significant relevant experience; or an equivalent combination of relevant experience and/or education/training. 1-2 years of proven experience as a Data Engineer or Data Scientist, focusing on working with healthcare datasets, such as MIMIC, EHRs, or other health information systems. Proficiency in SQL, Python, or other programming languages used for data manipulation and ETL processes. Experience with cloud platforms, such as AWS or GCP, for data storage and processing. Ability to collaborate effectively with interdisciplinary research teams, including non-technical stakeholders. Strong problem-solving skills and the ability to work independently in a fast-paced research environment. Detailed knowledge in the following areas, with significant experience in: Large Language Model Frameworks : Familiarity with the tools or frameworks supporting LLM development in applications (e.g., LangChain, Ollama, LlamaIndex), with a solid understanding of how to integrate and utilize these frameworks effectively in real-world solutions. Containerisation and Orchestration : Experience with containerisation (e.g., Docker) and orchestration tools (e.g., Kubernetes) for deploying and managing applications at scale, including support for GPU-accelerated applications. Data Engineering Tools : Proficiency in data engineering tools, including Apache Airflow for workflow orchestration, and message brokers like RabbitMQ or Kafka for handling real-time data streams. Cloud Infrastructure and DevOps : Ability to work with cloud platforms (e.g., AWS, GCP) and implement DevOps practices such as CI/CD pipelines, Infrastructure as Code (e.g., Ansible, Terraform), and continuous monitoring (e.g., Prometheus, Grafana). Database Technologies: Strong understanding of database systems, including SQL (e.g., PostgreSQL), NoSQL (e.g., MongoDB, Redis), and GraphDB (e.g., Neo4j, TigerGraph), with solid data modelling and query optimisation skills. Full-Stack Application Development: Experience in building and deploying full-stack applications that integrate data pipelines, APIs, and data-driven features. Machine Learning: Proficiency in using and coding with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and experience with cloud-based ML services (e.g., AWS SageMaker, Google AI Platform). The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, criminal check, education check. Relocating from interstate or overseas? We may support you with obtaining employer-sponsored work rights and a relocation support package. You can find out more about life in Australia’s Sunshine State here . Questions? For more information about this opportunity, please contact Dr Teerapong Leelanupab t.leelanupab@uq.edu.au . For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au , stating the job reference number (below) in the subject line. Want to Apply? We welcome applications from all individuals and are committed to an inclusive and accessible recruitment process. To be considered, please ensure you upload: Resume Cover letter Responses to the ‘About You’ section Our strength as an institution lies in our diverse colleagues. We're dedicated to equity, diversity, and inclusion , fostering an environment that mirrors our wider community. We're committed to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact talent@uq.edu.au . Other Information UQ is committed to a fair, equitable and inclusive selection process, which recognises that some applicants may face additional barriers and challenges which have impacted and/or continue to impact their career trajectory. Candidates who don’t meet all criteria are encouraged to apply and demonstrate their potential. The selection panel considers both potential and performance relative to opportunities when assessing suitability for the role. Applications close Monday 11 August 2025 at 11.00pm AEST (R-53443). Please note that interviews have been tentatively scheduled for the week commencing Monday 18 August 2025 .
