Clinical lab automation with AI-enhanced human robot interface for health practitioners

About this project 

This project aims to create an innovative human-robot interface that lets clinical lab practitioners, even without programming experience, to convey their workflow requirements in natural language for lab automation. Collaborative robots used in this project will be powered by a large language model, custom-trained for the pathology lab requirements, to tackle common workflow challenges. for the delivery of this project, the student will work closely with practitioners at SA Pathology to analyse the clinical workflow and certification process for improvement. The student will utilise GPU workstations, high performance computing, and cloud computing for AI-based code generation to control robots. 

This project provides an excellent opportunity to train the PhD student to apply AI for a practical challenge. The student will learn advanced large language model to generate robot software. This project also provides an opportunity for the student to learn the clinical workflow in real-world setup, to fine-tuning the code generation model.

What you’ll do 

With the development of a human robot interface that allows clinical practitioners to program robots using natural language, this project introduces the potential to make and test significant changes in the pathology workflow, leading to a new paradigm that revolutionises clinical lab automation. Clinical practitioner will no longer be required to communicate their requirements to robot experts; instead, they can focus on setting up of a working prototype that directly support their need. Meanwhile, robotic experts will focus on auditing the software to ensure the functionality. Expected outcomes are: (1) improved efficiency in designing and deploying clinical lab automation, and (2) broader adoption collaborative robotics in clinical laboratories. 

Where you’ll be based

Sustainable Infrastructure and Resource Management (SIRM)

Ivan Lee is an expert in intelligent sensor, multimedia system, and data science. Ivan currently serves as the Technology Development Leader of UniSA Research Concentration of Sustainable Infrastructure and Resource Management (SIRM). He is a member of Science Advisory Committee (SAC) of the National Computational Merit Allocation Scheme (NCMAS), and a member of X-ray Imaging Methods Working Group, Future Lightsource (4th Generation Synchrotron) of The Australian Synchrotron. Ivan was named to the list of Research Field Leaders by The Australian Research Magazine 2024. He was a REDI Fellow in 2022/2023. 

Sarvnaz Karimi is a Principal Research Scientist at CSIRO’s Data61. She has over a decade of experience developing and applying methods in the intersection of Information Retrieval (IR), Natural Language Processing (NLP), and Machine Learning for specific domains, such as health, mental health, emergency situation awareness and climate adaptation. She has supervised and mentors multiple PhD students and postdoctoral fellows over years in collaboration with CSIRO colleagues and different universities across Australia.

Peter O’Loughlin is a chemical pathologist Chief Innovation Scientist at SA Pathology, and an Adjunct Clinical Professor at UniSA. Financial Support 

This project is funded for reasonable research expenses. Additionally, a living allowance scholarship of $47,020 per annum is available to Australian and New Zealand citizens, and permanent residents of Australia, including permanent humanitarian visa holders. Australian Aboriginal and/or Torres Strait Islander applicants will be eligible to receive an increased stipend rate of $52,352 per annum (2025 rate). A fee-offset or waiver for the standard term of the program is also included. For full terms and benefits of the scholarship please refer to our scholarship information. International applicants are not invited to apply at this time.

Eligibility and Selection

This project is open to applications from Australian or New Zealand citizens, and Australian permanent residents or permanent humanitarian visa holders. International applicants are not invited to apply at this time.

Applicants must meet the eligibility criteria for entrance into a PhD. 

All applications that meet the eligibility and selection criteria will be considered for this project. A merit selection process will be used to determine the successful candidate.

The successful applicant is expected to study full-time or part-time, and to be based at our Mawson Lakes Campus in the north of Adelaide. 

Essential Dates 

Applicants are expected to start in a timely fashion upon receipt of an offer. Extended deferral periods are not available. Applications close on Monday 26 May 2025.