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infectious disease data using statistical and/or mathematical approaches would be highly desirable. Experience in statistical analysis, and proficiency in statistical and computer modelling software (e.g. R
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an outstanding research track record and extensive expertise in cancer bioinformatics, cancer biology, cancer immunology, deep learning models and/or artificial intelligence, as well as hands-on experience with
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, molecular and cell biology, and animal models. Skills in bioinformatics are advantageous. Candidates should be highly motivated and have a track record of publications in international journals. The appointee
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immunology, deep learning models and/or artificial intelligence, as well as hands-on experience with cell culture, cellular/molecular biology, and animal studies. The ideal candidate should be self-motivated
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the field of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R
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, tissue culture or primary cell culture models, b) ability to work with infectious small animals, or c) omic-science. The appointee will conduct research projects related to emerging agents of hepatitis
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, including 3D modelling, physics integration, and cross-platform deployment (PC, mobile, AR); integrating and deploying AR navigation applications on Microsoft HoloLens, covering spatial mapping, SLAM
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, and assessing the impact on disease progression. Develop relevant disease models to assess therapeutic efficacy of a specific treatment. Demonstrate understanding of the disease pathology for better