生物统计学的博士主要做什么？
PhD in Biostatistics 的学习内容，根据学校、导师及项目的不同而有所区别，但一般主要包括以下课程：
Calculus， Differential equations， Linear Algebra， Probability Theory， Statistics， R， Python等基本计算和编程类；
Quantitative methods in the biological sciences， Statistical models and design of experiments， Advanced Regression and Time Series， Survival Analysis， Longitudinal Data Analysis， Machine Learning， Big Data， Databases等统计和数据科学的相关内容。
除了学习以上课程外，PhD students 还需要完成一篇论文（dissertation）来展示他们对于所研究方向的理解程度和科研能力。在撰写paper的过程中，学生将学习到如何提出假设、设计实验/研究方案、获取数据、处理分析数据并得出结论。在毕业答辩时，学生需要向委员会展示自己对于该领域知识、理论和实践方法掌握的全面性以及运用所学知识进行独立研究和解决难题的能力。
PhD in biostatistics is a broad discipline that covers multiple areas in statistics with diverse applications. The goal of this degree is to provide students with rigorous training in statistical theory and methods so that they can adapt these tools to solve problems related to life science research and biomedical decision making. In addition to studying theories and methods， graduate-level courses in biostatistics cover practical issues such as ethical considerations for research and how to design studies to ensure validity and reliability of findings．All these elements come together when students complete an independent research project， which results in their final thesis or dissertation.
The field of biostatistics has many applications in health care and biomedical research. It involves using mathematical and computational approaches to analyze data from clinical trials， observational studies or genome-wide association studies to answer important questions about human health and disease. Examples include the study of drug safety and efficacy to determine whether new medications work well in humans (e.g.， to treat cancer)， identifying risk factors for chronic diseases like diabetes or cardiovascular disease， or understanding the underlying causes of complex disorders like autism spectrum disorder或 attention deficit hyperactivity disorder (ADHD).
To be successful in biostatistics， candidates need to have strong quantitative skills with