计算机科学哲学博士-健康信息学

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The David R. Cheriton School of Computer Science has an international reputation in teaching, academics, research, and employment. We attract exceptional students from all over the world to study and conduct research with our award-winning faculty. You can participate in research projects in a wide variety of topics with our internationally acclaimed researchers. Our research spans the field of computer science, from core work on systems, theory and programming languages to human-computer interaction, DNA and quantum computing to theoretical and applied machine learning, just to name a few. As a graduate student, you will: Access research-intensive lab spaces. Gain the opportunity to publish your work in top conferences and journals. Present at premier conferences in front of peers, industry leaders, researchers, and experts in your field. As a graduate student, you will have the independence to pursue your preferred area of research with a faculty If you want to continue pursuing research and expand your learning, you will work with a supervisor to develop a thesis. As a graduate student at the PhD level you will be expected to conduct meaningful research that expands the scope of your graduate work.<br><br>Technological innovations that represent significant advances in the practice of medicine are announced almost daily. Many of these innovations stem from the field of health informatics, a field that seeks to enhance the human condition and the delivery of healthcare by applying methods and theories drawn from computer science. The research questions we explore represent the full spectrum of health informatics, ranging from scientists whose work contributes to a better understanding of how to cure disease, through to those whose efforts explore how approaches anchored in computer science can enable people to live healthy lives. Representative problem domains of current projects include medical image processing, genomic analysis, assistive technologies for older adults, natural language generation of tailored treatment descriptions, data mining of electronic health records, chronic disease monitoring by wearable sensors, software engineering, privacy-enhancing technologies, computational neuroscience, human-computer interaction, and ubiquitous computing.