Research Associate/Post-doctoral Fellow in infectious disease modelling and bioinformatics
Laboratory of Data Discovery for Health Limited
- Hong Kong
- Permanent
- Full-time
- Possess a Ph.D. (and/or Master's) degree in Bioinformatics, Computational Biology, Statistics, Systems Biology, Infectious Disease Modelling, or related disciplines;
- All projects require proficiency in at least one programming/scripting language (e.g., Python, R, MATLAB, Java, C++/C), along with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch) and environments (e.g., Ubuntu). Familiarity with the Linux system is desirable but not required;
- Understanding basic principles of genetics, cell biology, virology, immunology, epidemiology and/or public health because most projects involve interdisciplinary research and close interactions with local and international collaborators;
- Demonstrate publication records in notable conferences and impactful medical or interdisciplinary journals (as first or senior author within the past 3-5 years);
- Possess experience in machine learning techniques, including deep learning, neural networks, and statistical/mathematical modeling, with a focus on applying these techniques to clinical and epidemiological data; and
- Familiarity with clinical terminologies, Electronic Health Records (EHRs), and healthcare data standards is preferred.
- 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;
- Experience in integrating data from various sources, including genomics, immunology, epidemiology and/or public health;
- Experience working with 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;
- Possess excellent written, interpersonal, and verbal communication skills, with the ability to present complex technical concepts to both technical and non-technical stakeholders; and
- Be able to collaborate effectively with multidisciplinary teams, including clinicians, data scientists, software engineers, and healthcare stakeholders, to understand requirements and translate them into technical solutions.
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