The Biostatistics PhD program emphasizes both didactic and experiential learning. Program years 1 and 2 will include theoretical and applied classroom work in the core mathematical statistics and biostatistics courses, with additional electives in mathematics and/or computer science, and in the life sciences. The core courses incorporate classroom projects in theory and data analysis, and introduce literate programming and reproducible research practices. Year 2 requires a set of Biostatistics Rotations under the tutorship of a faculty mentor, using data drawn from collaborative projects in biomedical or public health sciences, with required oral and written presentations. The student will select, by the end of year 2, a primary advisor from among participating program faculty. Additional training in the biomedical area of application will occur in years 3 and 4. Throughout, the student will participate in presentations and discussions in a seminar series and journal club. The PhD thesis, completed in years 3-4 and potentially 5, will contain an original contribution of quality that would be acceptable for publication in the biostatistics literature, which extends the theory or methodology of biostatistics, or extends biostatistical methods to solve a critical problem in applied disciplines.