Students learn how to process imperfect biomedical measurements and extract information. Students learn fundamental principles of signal and image processing and machine learning. Prerequisites: Ability to program in MATLAB or Python. Knowledge of calculus, vectors and matrices

A professional development course for biomedical engineering graduate students.

Applies engineering science, design methods, and system analysis to developing areas and current problems in biomedical engineering. Topics vary by semester.

Provides biomedical engineers with a grounding in molecular biology and a working knowledge of recombinant DNA technology, thus establishing a basis for the evaluation and application of genetic engineering in whole animal systems. Beginning with the basic principles of genetics, this course examines the use of molecular methods to study gene expression and its critical role in health and disease. Topics include DNA replication, transcription, translation, recombinant DNA methodology, methods for analyzing gene expression (including microarray and genechip analysis), methods for creating genetically-engineered mice, and methods for accomplishing gene therapy by direct in vivo gene transfer. Prerequisite: BME 6103, undergraduate-level cell and/or molecular biology course. (e.g., BME 2104) or instructor permission. Suggested preparation: biochemistry, cell biology, genetics, and physiology..

For master's students.

FOR GRAD STUDENTS ONLY. A research project in biomedical engineering conducted in consultation with a faculty advisor. Includes the design, execution, and analysis of experimental laboratory work and computational or theoretical computer analysis of a problem. Fulfills the project requirement for the Biomedical Engineering Masters of Engineering degree. Prereqs: Instructor Permission Required.

Master's Research

Formal record of student commitment to doctoral research under the guidance of a faculty advisor. May be repeated as necessary.