Biostatistics, PhD

Program Overview

The PhD program in Biostatistics at Johns Hopkins University provides comprehensive training in biostatistical methodology, data science principles, and practice. The program equips graduates with strong capabilities in original research, statistical software development, and public health problem-solving. It offers a rigorous curriculum balancing theoretical foundations with advanced applications and prepares students for research-intensive careers in academia, industry, and government.

Program Outline

Degree Overview:

The PhD program in Biostatistics at Johns Hopkins University provides comprehensive training in biostatistical methodology and practice, encompassing both theoretical foundations and advanced data science applications. The program distinguishes itself by its broad emphasis, spanning from the fundamentals of statistical reasoning to data science principles and practice. It offers rigorous training in both real analysis-based probability and statistics, comparable to what is offered in most departments of mathematical statistics. The program aims to prepare individuals with strong backgrounds in mathematics, engineering, and natural or social sciences to become research biostatisticians in academia, industry, or government. The program's objectives are to equip graduates with the following capabilities:

• Conduct and publish original research on the theory, methodology, and practice of biostatistics and data science.
• Translate methodological advancements into software and other tools to disseminate them into practice.
• Apply innovative theory and methods to address public health problems.
• Serve as expert biostatisticians and data scientists on collaborative research teams addressing key public health questions.
• Teach biostatistics and data science effectively to health professionals, scientists, and graduate students in biostatistics.

Outline:

The PhD program in Biostatistics at Johns Hopkins University is structured around a core curriculum and elective courses. The core curriculum consists of three main components:

• Biostatistical Methodology (Methods): This component comprises a one-year sequence of advanced-level courses in biostatistics, covering topics such as statistical inference, regression analysis, survival analysis, and longitudinal data analysis.
• Probability and Statistical Theory (Theory): This component includes a one-year sequence of introductory-level courses in probability and statistical theory, followed by a one-year sequence of advanced-level courses in probability theory and statistical theory.
• Data Science: This component involves a one-year sequence of introductory-level courses in data science, covering topics such as statistical computing, programming paradigms, and data science applications in public health.
Students can choose between two advanced-level data science sequences: one focusing on statistical machine learning and the other on advanced statistical computing.

Course Schedule:

The program requires students to complete a total of 30 credits, including:

• 14 core courses: These courses must include at least one year of Methods, one year of Theory, and one year of Data Science.
No more than four introductory-level courses are allowed.
• 16 credits of advanced PhD elective courses: These courses allow students to specialize in areas of interest within biostatistics.
• 18 credit units of formal coursework outside the Department of Biostatistics: At least nine of these credits must be taken in the School of Public Health.
• Required courses: Current Topics in Biostatistics Research (140.860), Academic & Research Ethics at BSPH (550.860), Responsible Conduct of Research (550.600), and Epidemiologic Inference in Public Health I (340.721).

Assessment:

The program utilizes a comprehensive assessment system to evaluate student progress and ensure mastery of the curriculum. Key assessment components include:

• First-year Departmental exam: This written exam is administered at the end of the first year and assesses students' understanding of core biostatistical concepts and methods.
• Practice oral exam: This exam is typically taken no later than six months after the end of the fourth term of the second year and evaluates students' ability to communicate statistical ideas and concepts.
• Preliminary oral examination: This exam is typically taken at the beginning of the third year and involves a presentation and discussion of the student's thesis proposal.
• Oral thesis defense: This public forum is held at the end of the program and involves a defense of the student's completed thesis.

Teaching:

The Department of Biostatistics employs a variety of teaching methods to facilitate student learning, including:

• Lectures: These provide a structured framework for introducing key concepts and theories.
• Problem sets: These allow students to apply their knowledge and develop problem-solving skills.
• Discussions: These foster critical thinking and encourage students to engage with the material in a collaborative setting.
• Seminars: These feature presentations by leading statistical scientists from around the world, exposing students to cutting-edge research and advancements in the field.
• Teaching assistantships: PhD students are required to apprentice with faculty as teaching assistants, gaining valuable experience in teaching and mentoring.

Careers:

The PhD program in Biostatistics at Johns Hopkins University prepares graduates for a wide range of career opportunities in the field of biostatistics and data science. Potential career paths include:

• Research biostatistician: This role involves designing and conducting statistical analyses for research studies in various fields, including public health, medicine, and pharmaceuticals.
• Data scientist: This role involves applying statistical and computational methods to analyze large datasets and extract meaningful insights.
• Biostatistical consultant: This role involves providing statistical expertise to organizations and individuals in various sectors, including healthcare, government, and industry.
• Academic faculty: This role involves teaching and conducting research in biostatistics at universities and research institutions.

Other:

The Department of Biostatistics offers a weekly seminar program featuring recent work by outstanding statistical scientists from around the world. Attendance is required for all graduate students. One seminar per month may be designated to be part of the Biostatistics "Grand Rounds" series, which features statistical analyses addressing important public health questions. The program provides full funding for tuition and stipend for five years. Students are expected to finish their doctoral programs within this time. Students who do not finish within five years may continue in the program for up to two additional years with a 75% departmental tuition scholarship. The Department is committed to providing every opportunity for its students to successfully complete the academic program of their choice. To support students in progressing toward the degree and to further their educational experience, the Department offers a comprehensive written examination at the end of the first year and a practice oral exam, usually taken no later than six months after the end of the fourth term of the second year.