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join a multidisciplinary team led by the Principal Investigator to develop AI‐driven navigation systems in robotic implant surgery. The duties include but not limited to: designing, implementing, and
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surgery. The duties include but not limited to: designing, implementing, and optimizing high-performance C++/C# software modules for real-time control, sensor fusion, and data analysis; developing unity
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proficient in data analysis using statistical or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic
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or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic research papers. They should be organized, self
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record of publications in relevant fields. Have proficiency in data processing and statistical analysis, with experience in programming languages/software such as MATLAB, Python, R, Stata, as well as GIS
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quantitative research methods. Demonstrate strong research capability and a track record of publications in relevant fields. Have proficiency in data processing and statistical analysis, with experience in
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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Responsibilities The appointee will join a multidisciplinary team led by the Principal Investigator to develop AI‐driven navigation systems in robotic implant surgery. The duties include but not limited
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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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the Department of Clinical Oncology, School of Clinical Medicine (Ref.: 532723) Applicants should process a Ph.D. degree preferably in Cancer Genetics, Cancer Biology, Biological and Biomedical Sciences or a