Post-doctoral Fellow in the Department of Family Medicine and Primary Care, School of Clinical Medicine (Ref.: 529962), to commence as soon as possible for two years, with the possibility of renewal subject to satisfactory performance and funding availability. Information about the Department can be obtained at https://fmpc.hku.hk/.
The appointee will have the opportunity to join a highly interdisciplinary research team led by Dr. Jayden Jiandong Zhou, which involves interdisciplinary research and close interactions with local and international collaborators including Medical Professionals, Hepatologist, Epidemiologist, Data Scientist, Software Engineers, Health Economists, and other clinical staff and healthcare stakeholders, in the field of Family Medicine and Primary Care.
The appointee will work on various projects related to sexual health, infectious diseases, and/or health promotion, with the major contributions to developing and implementing a personalized Artificial Intelligence (AI) program system that improves liver health management by accurate prevention, diagnosis, and tailoring treatment plans to the individual characteristics of patients with chronic hepatitis B infection. The initiative seeks to harness the power of advanced AI technologies to analyse multi-modal health data, recognize patterns specific to liver diseases, and predict the best possible interventions tailored for each unique patient scenario, with four specific studies:
- Develop knowledge representation from multi-modal datasets (tabular EHR data, texts, images) of patients with chronic hepatitis B infection using advanced AI and Large Language Models (LLMs).
- Development and validation of personalized AI models for early diagnostics and risk stratification of progression risks among patients with chronic hepatitis B infection.
- Heterogeneous treatment effects modelling for precise liver disease management.
- Personalized AI-based traditional Chinese medicine (TCM) in hepatology.
Requirements:
- Possess a Ph.D. degree in Data Science, Computer Science, Electronic Engineering, Artificial Intelligence, Biomedical Engineering (Health Informatics and/or Bioinformatics), Medical Statistics, Public Health and Epidemiology, and other majors related with AI in Hepatology and Gastroenterology (or other infectious diseases).
- Experience working with multi-modal clinical data, especially Electronic Health Record (EHR) data, including preprocessing, handling unstructured text data, structured records, and extracting meaningful information from clinical notes, discharge summaries, and other sources.
- Experience in clinical text mining and image patterns recognition, using AI and LLMs approaches.
- Good understanding basic diagnosis and management of chronic hepatitis B infection, liver cancer, and other liver-related complication diseases, and understanding basic principles of statistics, machine learning, and LLMs.
- Proficiency in at least one programming/scripting language (e.g., Python, R), along with strong experiences in relevant libraries and frameworks (e.g., TensorFlow, PyTorch) and computation environments (e.g., Ubuntu).
- Demonstrate publication records in notable conferences and impactful clinical/medical or interdisciplinary journals (as first or senior author within the past 3-5 years).
- Responsible and highly self-initiated, with the ability to work independently and as part of an interdisciplinary team, with the ability to present complex technical concepts to both technical and non-technical stakeholders.
- Outstanding experiences in knowledge sharing, organizational skills and demonstrated ability to complete tasks in a precise and detailed manner.
- Excellent communication and interpersonal skills to interact effectively with the team and collaborators.
- Fluency in both written and spoken English is a must.
Desirable Abilities:
- Possess in-depth knowledge and a proven track record of successfully designing, implementing, and deploying mathematical and statistical models and systems for real-world applications in the healthcare domain.
- Relevant research and work experiences in screening, diagnosis and management of liver diseases (e.g., chronic hepatitis B infection, metabolic dysfunction-associated or nonalcoholic fatty liver disease, hepatocellular carcinoma) would be desirable.
- Familiarity with clinical terminologies, EHR systems, and healthcare data standards in Hong Kong.
- Familiarity with the Linux system (e.g., Ubuntu).
- Proficiency in both written and spoken Chinese.
Responsibilities:
- Development of knowledge representation approaches from liver-related multi-modal datasets including Electronic Health Records tabular data, clinical texts, and image data of ultrasonography, computed tomography, magnetic resonance imaging, using advanced AI and LLMs.
- Fine-tuning and prompt engineering for Large Language Models.
- Participate in the development and validation of machine learning models for the early diagnostics and risk stratification of progression risks (MAFLD/NAFLD, HCC recurrence, other complications, etc) among patients with chronic hepatitis B infection.
- Participate in the development and validation of heterogeneous (individualized) treatment effects modelling using casual machine learning models (and compare with traditional statistics-based casual analysis models).
- Contribute to the development and validation of personalized AI-based TCM in hepatology, including TCM herbal medicine formulation, TCM knowledge representation, herbal medicine recommendation system, etc.
- Contribute to research activities, assisting in literature review, health data cleaning, data analysis, methodology/results interpretation, and manuscript writings.
- Conduct systematic searches and comprehensive literature reviews, code and analyse both qualitative and quantitative data for meaningful insights, and present feedback based on research findings.
- Designing or developing websites, mobile applications, or software modules for hospital EHR system use.
- Drafting reports, writing grants, or other duties assigned by the project leader.
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 at the University's career site (https://jobs.hku.hk) and upload an application letter and a detailed up-to-date CV. Review of applications will start as soon as possible and continue until September 30, 2024, or until the post is filled, whichever is earlier.
The University is an equal opportunities employer and
is committed to equality, ethics, inclusivity, diversity and transparency
