Senior Research Assistant in the Division of Epidemiology and Biostatistics

Senior Research Assistant in the Division of Epidemiology and Biostatistics, School of Public Health (Ref.: 532533), to commence on 1 November 2025 or thereafter, on a one-year temporary term contract, with the possibility of renewal subject to satisfactory performance and funding availability.

Applicants should possess:

1. a Master's degree or above in Computer Science, Computational Linguistics, Machine Learning, Natural Language Processing (NLP), Statistics, or a related discipline;
2. strong programming skills in Python, R, Java, or C/C++ are essential, along with at least 1 year’s post-qualification experience in using relevant libraries and frameworks (TensorFlow, PyTorch, scikit-learn) and environments (e.g. Ubuntu, BRAT);
3. extensive experience with deep learning architectures, machine learning techniques, statistical modelling, and prompt engineering, applied to healthcare-oriented NLP tasks - including text classification, named entity recognition, text generation; and
4. a strong track record of working with EHR data and developing NLP applications for lupus-related research.

The appointee will contribute to research projects at the intersection of natural language processing (NLP) and clinical medicine. Key responsibilities include:

1. applying regex and related techniques for data deanonymization and text pre-processing;
2. selecting diverse, representative samples from sparse populations;
3. designing and developing language model-based systems for assisting annotators in annotating lupus-related clinical features;
4. working with electronic health records (EHRs) and other clinical documents to extract meaningful information from unstructured text (e.g. clinical notes, discharge summaries);
5. implementing, evaluating and deploying NLP-based scoring systems for real-world clinical notes for the lupus disease;
6. prompting and training large language models (LLMs) through supervised fine-tuning or reinforcement learning techniques;
7. preparing project plans, IRB applications, and supporting documentations;
8. coordinating team communication, organizing meetings, and recruiting and managing annotators; and
9. collaborating with multidisciplinary teams, including clinicians, data scientists, software engineers, and healthcare stakeholders, to translate clinical and research needs into technical solutions.

Enquiries about the duties of the post should be sent to Ms Audrey Ho at audreyh@hku.hk. Information about the School can be obtained at https://sph.hku.hk/.

A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.

The University only accepts online application for the above post. Applicants should apply online and upload an up-to-date CV. Review of applications will start as soon as possible and continue until 3 October 2025, or until the post is filled, whichever is earlier.