Post-doctoral Fellow
The University of Hong Kong
Apply now Ref.: 529962
Work type: Full-time
Department: Department of Family Medicine and Primary Care, School of
Clinical Medicine (22500)
Categories: Senior Research Staff & Post-doctoral Fellow
Hong Kong
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
Advertised: Sep 13, 2024 (HK Time)
Applications close: Sep 30, 2024 (HK Time)
Apply now
