Data Science and Computation Graduate Track

Data Science and Computation engineering, which includes computational synthetic biomedical engineering, is an emergent field that combines experimental, computational, and theoretical methods to solve challenging biomedical problems. Data Science and Computation engineering is based on a holistic approach of integrating large amounts of molecular information to elucidate the relationships between genotype and phenotype. This multiscale understanding of biological systems will help answer important questions about physiological systems, human disease, and therapeutic strategies. Data Science and Computation engineering is the design and construction of biological systems from molecular biological components for useful purposes. Such systems have applications in a wide range of complex biomedical problems.
Among the greatest challenges in these fields are how to obtain, manipulate, and interpret massive datasets. Research in this area also requires a multi-scale understanding of the system of interest, from molecules to cells, to organisms to ecosystems. Data Science and Computation engineering draw from a wide range of specialties – including mathematical modeling, scientific computing, signal processing, molecular biology, and high-throughput technologies – to provide a unique approach to solving biomedical problems.

M.S. students in the Data Science and Computation track must successfully complete the core course requirements outlined in the Handbook, as well as the total course credit hour requirement of the M.S. degree programs.

Ph.D. students in the Data Science and Computation track are expected to have general knowledge in computational and numerical methods as well as in systems and synthetic biomedical engineering, with a specific focus in one biomedical engineering application. A student who, for example, applies computational methods to problems in cancer genomics, should have knowledge in both areas. The material for the exam will be based primarily on topics covered in the core courses. However, there will be a strong emphasis on the integration of computational approaches and the target area of application, material not likely to be covered explicitly in any course or textbook.

The course selection that will be appropriate for each student in the Data Science and Computation track will vary and depend highly on the specific research project in which the student participates. It will be especially important to choose courses that provide both the scientific background and the technical skills required to carry out this research. The Program of Study is a list created by the student and the supervisory committee of all courses to be completed by the student as part of the requirements for the Ph.D. The Program of Study requires formal approval by the student’s advisor, Dissertation Supervisory Committee, and Director of Graduate Studies.

For more detailed information, please review the BME Graduate Resources page and select the Graduate Handbook that correlates to the year you started your program.

Please contact Dr. Orly Alter or Dr. Tamara Bidone.