About UNSW:

UNSW Medicine & Health is a national leader in learning, teaching and research, with close affiliations to several of Australia’s finest hospitals, research institutes and health care organisations. With a strong presence at UNSW Sydney campus, the faculty have staff and students in teaching hospitals in Sydney as well as regional and rural areas of NSW including Albury/Wodonga, Wagga Wagga, Coffs Harbour and Port Macquarie. 

Details of the role

This Data Scientist role offers a unique opportunity to work at the intersection of artificial intelligence, machine learning, and healthcare. The role will contribute to designing and implementing AI-driven solutions to automate ICD-11 coding from Emergency Department (ED) data, which include structured fields and free text clinical notes.

The appointee will lead the fine-tuning of advanced Large Language Models (LLMs) while ensuring the reliability, accuracy, and compliance of the solution. Your expertise will help create a pipeline that contributes to reporting of injury related presentations to EDs, predominantly by jurisdictional health departments. 

The role will collaborate with clinicians, coders, engineers, and researchers to align solutions with healthcare workflows, working closely with the broader research team partners including CSIRO and AIHW. .

The role reports to the Senior Research Fellow and Chief Investigator of this MRFF National Critical Research Infrastructure grant funded work with a dotted reporting line to a Senior Data Scientist at the CSIRO. There are no direct reports. 

Some key skills required:

• PhD or Master’s in Data Science, Computer Science, Biostatistics, or related field with relevant experience or equivalent competence gained through any combination of education, training and experience.
• Fine-tune and validate Large Language Models (LLMs) to assign ICD-11 codes, evaluating their performance using precision, recall, F1, ROC-AUC, cross-validation, and other metrics.
• Detect and mitigate potential bias in AI models and uphold ethical AI standards by recommending and implementing strategies for bias detection and mitigation.
• Ensure compliance with privacy regulations (HIPAA, GDPR, local laws) and adhere to robust data governance practices for handling sensitive PHI and PII.
• Work with Emergency Department datasets, including structured fields and unstructured free-text data (e.g., triage notes).
• Assist in the development of Data Management Plans, Statistical Analysis Plans and other project related documentation. Demonstrated experience building machine learning pipelines; ≥2 years in healthcare, with knowledge of clinical data and medical vocabulary.
• Programming: Python (PyTorch, spaCy), SQL, shell scripting, and relevant knowledge in Natural Language Processing (NLP), including Transformer architecture and prompting methods.
• Excellent written and verbal communication skills, with proven ability to interact effectively with diverse stakeholders and present findings clearly to technical and non-technical audiences.

Desirable skills:

• Experience in clinical NLP, especially multi-label classification.
• Understanding of medical terminologies, coding systems, and standards (e.g., ICD-10/11, SNOMED CT).
• Knowledge of regulatory requirements and their implications for developing AI/ML solutions in healthcare.
• Experience in popular fine-tuning libraries of LLMs: Hugging Face transformers, Unsloth
• Experience with cloud-based platforms (AWS, GCP, or Azure).

Please refer to the position description for full details.

Pre-employment checks required for this position:

• Verification of Qualifications

UNSW Benefits and Culture 

• 17% Superannuation and leave loading​ 
• Flexible working ​ 
• Additional 3 days of leave over the Christmas Period​ 
• Access to lifelong learning and career development ​ 
• Progressive HR practices​ 

More information on the great staff benefits and culture can be found here.  

How to apply:

Please click on Apply now to apply online. Applications should not be sent to the contact listed below. Please provide a resume and a separate document addressing the skills and experience listed in the Position Description. A copy of the Position Description can be found on JOBS@UNSW.

Contact

Frank McHenry, Talent Acquisition Associate

E:  f.mchenry@unsw.edu.au    

Applications close: Thursday 19th February before 11.30pm Sydney time

UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.