Master of Science in Biomedical Engineering

Become an innovator in the biomedical engineering field.

With rapid advances in technology, and as generations live longer, more active lives, the demand for biomedical devices, procedures and other solutions continues to grow as well. Biomedical engineers with advanced degrees have even more opportunities for expanded responsibilities.

This 32-credit MS-BME program was designed to be flexible to serve both full-time students and working professionals seeking to become innovators in the biomedical engineering field. Students will have significant opportunities for research in state-of-the-art labs, working alongside accomplished faculty.

Graduates of the program will have the experience to perform research and engineering design for academia, government and industries related to human health. Additionally, students with the desire to continue on to a PhD program or professional medical education will have the appropriate basis upon which to build.

Upon successful completion of this program students will:

  • Gain the ability to demonstrate a breadth of knowledge in biomedical engineering
  • Have particular expertise in a field of biomedical engineering through coursework or research
  • Learn to use the techniques, skills, and modern engineering tools necessary for engineering practice
  • Demonstrate knowledge of contemporary issues in biomedical engineering with an emphasis on ethical questions
  • Students choosing the thesis option will gain research experience resulting in publishable work

Application Requirements

Program Information

Earn a master of science in biomedical engineering from Duquesne University in Pittsburgh, PA to advance your professional BME career.

Program Type




Required Credit Hours



The Master of Science Degree in Biomedical Engineering is a 32 credit program with or without thesis that provides breadth and specialized experience in BME. The thesis option culminates in research experience resulting in publishable work. The coursework for thesis and non-thesis options consists of a biomedical engineering core comprising 15 credits, 9 credits of approved electives, and two 1-credit seminars. For the thesis option, there are 6 credits of research. For the non-thesis option, 6 additional credits are taken in approved electives.

The ability to effectively disseminate current scientific ideas and research through both oral and visual presentations is a critical skill for engineering graduates. This course will focus on both effective presentation and evaluation skills. The course is a required BME MS course and will meet once a week.
The ability to effectively communicate scientific and engineering ideas is a critical skill for biomedical engineers. This course will focus on effectively communicating scientific ideas and interacting in a professional setting with both technical and nontechnical individuals. The course is a required BME MS course and will meet once a week. 
This introductory graduate course offers students a broad knowledge of modern methods and engineering tools used in biomedical engineering. Topics include MATLAB programming, 3D modeling/printing using Fusion 360, soft tissue characterization, optical sensing/imaging, FDA guidelines for medical device development/verification. This course features hands-on learning experience. Students will complete a group project after each module. In addition to projects, students will have opportunities to do experiments related to specific topics, such as tissue testing and optical imaging.
This course introduces mathematical and computational techniques that are relevant for describing and modeling physical processes encountered in biomedical engineering. Topics will include linear algebra and matrix methods, eigenvalues and eigenvectors, singular value decomposition, linear system of equations, and numerical methods for solving differential equations. Mathematical methods will be introduced within the context of current problems in biomedical engineering. This course makes extensive use of MATLAB computer programming to aid problem solving.
This course focuses on utilizing computational methods to solve engineering problems, which often can’t be solved analytically. The goal of this course is to provide students a comprehensive understanding of a variety of computational methods and algorithms. Those methods will be introduced in the context of engineering examples, and implemented in MATLAB. Advanced MATLAB programming techniques will be introduced to solve complex engineering problems. Topics of this course includes: errors, roots and optimization, curve fitting, integration, and differentiation. Advanced topics may also be introduced. 
This course provides a comprehensive introduction to modern biomedical imaging modalities that are currently employed in both biomedical research and clinical medicine. Imaging modalities covered in this course include optical imaging, X-ray radiography, computed tomography (CT), ultrasound, nuclear medicine (SPECT and PET), and magnetic resonance imaging (MRI). The main objective is to offer students a solid understanding of each imaging modality through lectures and assignments. For each imaging modality, we will focus on basic physics, image formation and reconstruction, imaging hardware, and applications. Image analysis and signal processing methods will also be briefly introduced. 
The principles and practice of tissue engineering will be the focus of this course. Topics include strategies for employing selected cells, biomaterial scaffolds, soluble regulators of gene expression, role of stem cells, and mechanical loading and culture conditions, Tissue fabrication techniques as well as the role of bioreactors in tissue development will be explored. Students will investigate using current literature the application of tissue engineering to specific organs.
Assessment and modification of the physical environment to enhance occupational performance including computer resources, assistive technology, home health, environmental controls, and environmental accessibility.
This introductory course will cover fundamentals of micro/nanotechnology and its applications in biomedical sciences. The course will provide rationale for utilizing micro/nanotechnology for biomedical applications including scaling laws. Basic microfabrication methods and design principles of microfluidics, lab-on-a-chip and microelectromechanical systems (MEMS) used in biology and medicine will be presented. Students will gain a broad perspective on applied research and commercial applications of biomedical microsystems.
This is an advanced course in the interdisciplinary field of biomedical microdevices. This course will build upon a fundamental understanding of the principles of micro- and nanoscale system design to explore state-of-the-art applications of biomedical microdevices. Students will learn about the cutting-edge micro/nanofabrication techniques and its most recent applications in biomedical sciences through in depth analysis of recent publications. 
This course addresses dynamic mathematical models of biochemical and genetic networks. Emphasis is on how modeling can enhance understanding of cell phenomena. Topics include chemical reaction networks, biochemical kinetics, signal transduction pathways with emphasis on receptor-mediated phenomena, and gene regulatory networks. Students will use current literature and programing to investigate specific models and their predictive power for biological and tissue engineering applications. 
Digital image processing is an indispensable component in biomedical research and imaging. The goal of this course is to provide students a solid understanding of a variety of image processing techniques and their implementations with a focus on biomedical applications. Image processing methods will be introduced primarily using MATLAB. Other image processing software, such as ImageJ and GIMP, will also be briefly introduced. Knowing multiple image processing platforms offers students the freedom to choose the most appropriate one to tackle specific image processing tasks. Topics of this course include: image filtering in spatial- and frequency-domain, image restoration and reconstruction, image transformation and registration, color image processing, and morphological image processing. 
This course provides an overview of FDA and select international regulations associated with medical devices, and those requirements to be followed when submitting one for approval or clearance. Examples of topic areas include: The Structure of the FDA and global approval agencies, Framework of regulatory approvals, Classification of medical devices for approval, Relevant US and international test methodologies, Guidance for conducting clinical trials, Good manufacturing practices and quality systems to be adopted, and Surveillance of medical devices. Individuals engaged in the development of medical devices and diagnostic tools, as well as those in healthcare studies wishing to learn more about their evaluation and approval, would benefit from information discussed in this course.