Computer Science + Biomedical Engineering

Listed on the application as: Interdisciplinary Computing: Neural Engineering 

Use computing and medical data to better understand the brain-body connection

Biomedical engineering (BME) brings engineering principles to medicine and healthcare, while computer science training provides the computational grounding to analyze complex biological data or build computational models that complement or realize engineering solutions. A student trained in both disciplines would be well-positioned to address data intensive challenges such as interpreting genomic data, developing machine learning algorithms for disease detection, or modeling physiological systems. 

Applications include software for medical imaging, computational simulations for drug discovery, and wearable devices for continuous health monitoring. Graduates of this combined program would be prepared for careers in biotechnology, medical device industries, healthcare analytics, or research.

What is neural engineering?

Neural engineering is the application of engineering principles, computational modeling, and advanced technology to understand, repair or enhance functions related to the human nervous system.

Neural engineers design technologies such as neuroprosthetics, deep brain stimulators, and adaptive brain-machine interfaces by combining neurophysiology with tools like digital signal processing, neural imaging, and bioinstrumentation. These innovations restore lost sensory and motor functions, improve the diagnosis and treatment of neurological disorders, and deepen our understanding of how the brain processes information.

What makes this program distinctive?

Several key areas of research, teaching, and industry collaboration at the University of Minnesota set the Computer Science + Biomedical Engineering subplan apart:

  • Neural Engineering Research Pillar: The UMN Department of Biomedical Engineering is a world-renowned leader in neural engineering. Students gain the computational foundation necessary to advance critical fields like brain-computer interfaces, deep brain stimulation, non-invasive neuromodulation, and neural decoding for prosthetics.
  • Interdisciplinary Research Infrastructure: Students learn alongside faculty experts who advance software for neuroimaging modalities and bioinstrumentation in our world-class research centers like the Institute for Engineering in Medicine and the Center for Magnetic Resonance Research,
  • Unmatched Medical Device Industry Connections: Located in Minnesota’s "Medical Alley"—one of the world's dense hubs for healthcare tech, medical devices, and digital health—the program offers direct exposure to industry leaders and real-world clinical applications.

Is Computer Science + BME right for me?

This subplan may be a good fit if you are interested in questions such as:

  • How can computational algorithms decode brain signals to control advanced prosthetics and neural interfaces?
  • How do machine learning models analyze complex biological and neuroimaging data to improve disease diagnosis?
  • How can computer simulation and software engineering improve the design and safety of life-saving medical devices?
  • Why are data-driven algorithms becoming essential for personalized medicine and adaptive neurotherapies?
  • How do researchers use signal processing and quantitative modeling to map human neural circuits and organ systems?

What can I do with this degree?

Graduates will be prepared to pursue careers and advanced study in areas including:

  • Medical-Device Software Engineer
  • Associate Test Engineer
  • Software Verification Engineer
  • R&D Engineer
  • Clinical Data Analyst
  • Bioinformatics Analyst
  • Medical Imaging Software Engineer
  • Clinical Informatics Analyst
  • Digital Health Software Engineer

Explore the curriculum

Learn more about admission requirements, required courses, and the recommended four-year plan for Interdisciplinary Computing: Neural Engineering.

Two students in a lab, with one looking into a microscope.

Expand your studies with the AI and Machine Learning minor

Students may also be able to complement this degree with the University of Minnesota’s new Artificial Intelligence and Machine Learning minor beginning in 2027.

The seven-course minor explores areas such as machine learning, data mining, computer vision, robotics, and natural language processing. Eligibility and course-planning requirements apply. Students interested in the minor should work with an academic advisor to determine how it can fit with their degree.

Explore the Artificial Intelligence and Machine Learning minor.