Biostatistics

Program Overview:

The University of California offers a comprehensive Biostatistics program designed to prepare students for a wide range of careers in health research, public health, medicine, and statistics. This program emphasizes the application of statistical methods to the biomedical and public health sciences, equipping students with the skills necessary to design studies, analyze data, and interpret results in a variety of healthcare settings. Students will engage in rigorous coursework that covers statistical theory, computational methods, epidemiology, and data analysis techniques relevant to modern healthcare challenges.

Throughout the program, students will have opportunities to work on real-world projects, collaborating with faculty involved in cutting-edge research in disease prevention, clinical trials, genetic research, and public health policy. The curriculum includes training in statistical software, programming languages such as R and SAS, and advanced methodologies like survival analysis, longitudinal data analysis, and Bayesian methods. Emphasis is also placed on ethical considerations in research, reproducibility, and effective communication of complex statistical information to non-statisticians.

Students can tailor their educational experience through elective courses in machine learning, bioinformatics, and health informatics. The program is designed for individuals with strong quantitative backgrounds seeking to expand their expertise in biostatistics or for professionals looking to enhance their analytical skills for health science research. Graduates of the program will be well-prepared for roles in academia, governmental agencies, healthcare organizations, and private industry, where data-driven decision-making is crucial. With a focus on practical applications and interdisciplinary collaboration, the university’s Biostatistics program aims to develop leaders who will advance public health outcomes through innovative statistical approaches.

PhD students are required to obtain  64 units of coursework from the following courses. For the MS degree the requirement is 52 units (48 units of required courses in Mathematical Statistics and Biostatistics and 4 units in Life Sciences). Full time graduate student must register for a minimum of 12 units per quarter. These 12 units can be made up of a combination of required coursework as described below, additional elective coursework if any, and special study courses (BST 251ABC). All student course programs, as well as any changes throughout the quarter, must be approved by a faculty advisor prior to registering for classes each quarter.

Required Courses (61 units) 

1. Two among the following courses:

   Required (Core) Courses in the Department of Mathematics (24 units)

   1. MATH 284 (Survival Analysis, 4 units)
   2. MATH 282 A, B (Linear Models, 4 units each)
   3. MATH 281 A, B,C (Mathematical Statistics I-II, 4 units each)
   4. Required (Core) Courses in Biostatistics (29 units) Each of:
      1. FMPH 221: Biostatistical Methods I (4 units)
      2. FMPH 222: Biostatistical Methods II (4 units)
      3. FMPH 223: Analysis of Longitudinal Data (4 units)
      4. FMPH 241: Biostatistics Rotation (2 quarters, 3 units each)
      5. FMPH 290: Biostatistics Seminar/Journal Club (3 quarters, 1 unit each)
      1. FMPH 224: Clinical Trials and Experimental Design (4 units)
      2. FMPH 225: Advanced Topics in Biostatistical Inference (4 units)
      3. FMPH226: Statistical Methods for Observational Studies (4 units)
      4. FMPH 227: Advanced Multivariate Methods (4 units)
   5. We note that all of the Biostatistics core courses except FMPH 290 carry a data analysis component. Students will be exposed to projects involving advanced data analyses to address complex life sciences problems. All courses except FMPH 290 are letter grade only.
   6. Required Life Sciences (8 units)
   7. Two courses at the upper division or the graduate level in Biomedical Sciences, Neurosciences, Epidemiology, Public Health, Biology, Systems Biology, Bioengineering, or Medicine, letter grade if possible. These courses are intended to provide the students with background in the life sciences and an introduction to complex life sciences problems that will constitute the area of application of their thesis and future research. The students are strongly encouraged to take further Life Sciences elective courses that are relevant to their research. Selection of all Life Sciences courses should be made in consultation with the thesis adviser.

Elective Courses (3 units)

Students are required to take at least 3 additional units of elective courses for letter grade from the following list.

1. Biostatistics Elective Courses
2. The Biostatistics elective courses are listed under one umbrella course number: FMPH 242, Advanced Topics in Biostatistics (3 units). This course is taught in rotation by the Division of Biostatistics and Bioinformatics faculty, and the curriculum will vary. Among the topics are:
   1. Random field theory and applications in image analysis
   2. Advanced Statistical Computing
   3. Bayesian methods
   4. Statistical collaboration in health sciences
3. Statistical Methods Electives:
   1. MATH 280 ABC (Probability Theory, 4 units)
   2. MATH 287 B (Multivariate Analysis, 4 units)
   3. MATH 287 D (Statistical learning, 4 units)
   4. MATH 287A, C (Time Series Analysis, 4 units each)
   5. MATH 202A (Applied Algebra I, 4 units)
   6. MATH 240ABC (Real Analysis, 4 units)
   7. MATH 271ABC (Numerical Optimization, 4 units)
   8. MATH 285 (Stochastic Processes, 4 units)
4. Computer Science Electives:
   1. CSE 202 (Algorithm Design and Analysis)
   2. ECE 273 (Convex Optimization, 4 units)
   3. CSE 250B: (Learning Algorithms, 4 units)
   4. CSE 255: (Data mining and predictive analytics, 4 units)
   5. CSE 260: (Parallel computation)
   6. CSE 283 (Genomics, Proteomics, Systems Biology, 4 units)

Biostatistics Rotations (FMPH 241) 

The Biostatistics Rotations are a singular feature of this PhD program that takes advantage of the extensive involvement of the program faculty in collaborative and interdisciplinary work within the Life Sciences. Students will complete at least two and up to five quarter-length rotations before advancing to candidacy, each in the form of an interdisciplinary applied data analysis project. They may work in collaboration with any UCSD faculty researcher who conducts studies or experiments which generate data in the medical, biological, public health or pharmacologic sciences, and who will serve as a subject area mentor, under the primary mentorship of any Biostatistics or Statistics member of the interdepartmental program. Each practicum will last a minimum of 10 weeks and will involve the analysis of original data. The student will prepare or substantially contribute to a project report, which will be reviewed and signed off on by the mentor. The rotation may be conducted as part of employment as a Graduate Student Researcher or as part of the dissertation research. A report based on an internship of at least 10 weeks duration at a facility, government health office, institute or company outside of UCSD focusing on biological or medical research can also be used to satisfy this requirement.

Requirements

• Statement of Purpose (details provided below)
• Transcripts (official transcripts will be required if admitted into the program); GPA >= 3.0 required for admission.
• List of mathematics and statistics courses taken/projected as well as textbooks used
• Three letters of recommendation; at least two should address academic and/or professional  qualifications for pursuing a PhD program in biostatistics. If more than three are received, the first three received will be reviewed.
• General Graduate Record Examination (GRE) test scores
• TOEFL test scores (for international applicants from non-English speaking countries)
• PhD Applicants Who Are U.S. Citizens are required to complete a FAFSA. This will assist in determining which applicants are eligible for grants that may have been awarded to support the interdepartmental program by various agencies and donors. FAFSA information plays no role in admission decisions.
• Curriculum vitae

Statement of Purpose

Your statement of purpose and objectives (1200-1500 word limit suggested) should address all of the following items:

• Describe those experiences that have shaped your interest in biostatistics. Do you have a preferred area of interest within the biostatistics discipline?
• Describe the one academic experience that has meant the most to you in your educational career.
• Outline your professional goals, both immediate and long term.
• Discuss why you are interested in the Biostatistics PhD program offered in the School of Medicine (Dept. of Family Medicine and Public Health, UCSD), the strengths you bring with you, and those areas in which you would like to increase your expertise and personal growth. Please specify if you have publications, work  or other experience which you feel makes you more likely to succeed in this program.

Financial Support

Qualified students will receive financial support for up to 5 years.

Students will be supported by:

1. Teaching Assistant Positions (generally first or second year students)
2. Graduate Student Research Positions (generally 3rd, 4th and 5th year students)
3. Biostatistics consulting positions in collaborative research (any level, depending on qualifications)
4. Potential NIH and NSF graduate fellowships

The University of California offers a comprehensive program in Biostatistics designed to equip students with the essential skills and knowledge required to analyze data in public health, medicine, and biological sciences. The program emphasizes the development of statistical reasoning, computational techniques, and an understanding of the underlying biological and health sciences. Students enrolled in the program are introduced to modern statistical methods, including regression models, survival analysis, Bayesian approaches, and data visualization, enabling them to interpret complex data sets effectively.

The curriculum typically combines theoretical coursework with practical applications, including laboratory work, statistical software training, and collaborative research projects. Students have access to state-of-the-art computing facilities and a wide range of resources for data analysis and statistical modeling. The program also fosters interdisciplinary collaboration, encouraging students to work with researchers from epidemiology, genetics, medicine, and other health-related fields.

Academic advising and mentorship are integral parts of the program, guiding students through their coursework, research initiatives, and career planning. Graduates of the Biostatistics program are well-prepared to pursue careers in academia, government agencies, healthcare organizations, and the biotechnology industry. They often engage in roles such as biostatisticians, data analysts, epidemiologists, and research scientists, contributing to public health initiatives and medical research.

The University of California's Biostatistics program is committed to fostering diversity and inclusion, providing opportunities for underrepresented groups, and promoting ethical research practices. Students also benefit from seminars, workshops, and conferences that provide exposure to cutting-edge research and networking opportunities with leading experts in the field.

Overall, the program aims to produce skilled biostatisticians who can translate complex data into actionable insights, ultimately improving health outcomes and advancing scientific knowledge. The program's combination of rigorous coursework, practical experience, and collaborative environment makes it a leading choice for students interested in the intersection of statistics and health sciences within the University of California system.