Key Responsibilities:
- Analyse and integrate healthcare data and public knowledge sources.
- Develop, fine-tune, and validate small LLMs to support clinical decision-making and interventions.
- Apply machine learning and NLP techniques to clinical narratives, biomedical text, and unstructured health data.
- Collaborate with clinicians to identify high-impact problems and translate them into technical solutions.
- Ensure data quality, security, and compliance with ethical AI principles.
- Contribute to publications and presentations on applied clinical AI and health data science.
- Participate in hospital/division initiatives and activities when assigned.
Job Requirements
- PhD in Data Science/Computer Science, or related discipline + 2 yrs post-doc experience.
- Excellent programming skills in Python.
- Proficiency with machine learning frameworks (scikit-learn, TensorFlow, PyTorch).
- Ability to communicate results clearly to clinical and non-technical audiences.
- Experience with and/or interest in novel deep learning architectures - e.g., fusion or energy-based models and fine-tuning large language models.
- Exposure to EHR data and healthcare data standards and ontologies (e.g., SNOMED CT, ICD, LOINC, HL7/FHIR).
- Familiarity with MLOps best practices.
- Prior experience in multi-disciplinary teams involving clinicians, researchers, and policymakers.
We regret to inform that only shortlisted candidates will be notified via email. Thank you for your application.
