医学生物物理学哲学博士-数据科学和计算生物学

研究生培训计划是医学生物物理学系的重要组成部分，其历史可以追溯到50年前，它起源于安大略省癌症研究所的癌症研究。该系提供硕士（MSc）和博士学位级别的跨学科研究型研究生课程。MSc程序是常见的切入点，但重点是PhD程序。本课程旨在扩大所有学生的学习背景，其中大多数人具有生命科学或物理科学的本科背景。<br> <br>医学生物物理学的研究人员结合了数学，统计学，计算机科学和机器学习的方法来进行分析和分析。了解这些大型数据集，其中包括来自基因组学，表观基因组学，转录组学，单细胞测序，蛋白质组学，数字病理学和医
The Department of Medical Biophysics is an interdisciplinary department with a strong history of excellence and discovery in cancer research, treatment, and beyond. Located primarily at the Princess Margaret Cancer Centre, Sunnybrook Research Institute, and SickKids Research Institute, the department offers research training leading to the Master of Science and Doctor of Philosophy degrees. The multidisciplinary program in cancer research and broader biomedical research cuts across the conventional boundaries of biology, physics, translational medicine and engineering to deliver a modern, advanced academic curriculum and world-class research training.<br>In this specialization within our PhD program, students complete a thesis-based PhD, while completing a structured medical physics course curriculum. The specialized program provides a research-intensive environment that immerses students in clinical technologies pertinent to medical imaging, such as computed tomography, magnetic resonance imaging and nuclear medicine, and radiation therapy. Cutting edge research involving machine learning, theranostics, and heavy particle therapy are ongoing. Students gain skills to pursue the production of high quality research and develop leadership skills.<br>Huge streams of data are constantly being collected, but how can we make sense of this data and use it to our advantage. Medical Biophysics researchers combine methods from mathematics, statistics, computer science and machine learning to analyze and understand these large datasets, which include data from genomics, epigenomics, transcriptomics, single cell sequencing, proteomics, digital pathology and medical imaging. A large portion of current MBP research is looking at how we can use large-scale data to develop algorithms or models to understand biological systems and relationships, specifically targeted at the diagnosis and treatment of disease.