Skip to main content

Merge Computer Science with Neuroscience

 

The Neuroscience+CS program integrates a cutting-edge computer science education with a top-notch neuroscience program, preparing you to innovate in computer science, neuroscience, and the combination of the two, including neural networks, cognitive computing, and computational neuroscience.

Model Neural Networks

Analyze Biomedical Data

Advance Cognitive Computing

Innovate the Future

As a graduate of the Neuroscience+CS program, you will be poised for careers in biomedical research, healthcare technology, and artificial intelligence. With expertise in both fields, you’ll have the potential to contribute to groundbreaking research and development in related fields, including healthcare diagnostics, brain-machine interfaces, and neural prosthetics.

Personalize Your Neuroscientific Studies

 

With a range of electives in neuroscience and computer science, you can tailor your studies to specific interests, such as neural networks or the computational brain. This customization ensures you will acquire the skills needed for your desired career path, making your education both relevant and personal.

Merge Computing with Brain Science

The Neuroscience+CS integrated bachelor’s degree, a partnership between the Department of Computer Science and the Department of Neuroscience, prepares you to innovate in neuroscience, computer science, and at the intersection of the fields. Preparing you to pioneer innovations that can change the world of brain research, healthcare, or computing.

Sample Course Sequences

Note: The course sequence provided is a sample schedule. Students should consult with their academic advisor to customize their coursework based on course availability, academic interests, and transfer credits.

Fall 

  • CS 312 Introduction to Computer Programming

  • M 408C or 408N Calculus 1

  • CH 301 Principles of Chemistry I

  • BIO 311C Introduction to Biology I

  • UGS 302 or 303 First Year Signature Course (UT Core)

Spring

  • CS 311 Discrete Math

  • CS 314 Data Structures

  • M 408S Calculus 2

  • CH 302 Principles of Chemistry II

  • CH 204 Introduction to Chemical Practice

  • BIO 311D Introduction to Biology II

Fall

  • CS 429 Computer Architecture

  • SDS 321 Introduction to Probability and Statistics

  • BIO 325 Genetics

  • BIO 206L Intro Labs Experiment in Biol

  • Varies Social and Behavioral Science Course (UT Core)

Spring

  • CS 439 Operating Systems

  • M 340L Matrices and Matrix Calculations

  • NEU 330 Neural Systems I

  • RHE 306 Rhetoric and Writing 

  • Varies Visual and Performing Arts Course (UT Core)

Fall 

  • CS 331 Algorithms and Complexity

  • PHY 317K & 105M General Physics I

  • NEU 335 Neural Systems II

  • GOV 310L American Government (UT Core)

  • Varies US History (UT Core)

Spring

  • CS 342 Neural Networks 

  • NEU 466M(T?) Quantitative Methods In Neuroscience I

  • Varies Neuroscience Upper Division Elective #2

  • PHY 317L & 105N General Physics II

  • Varies US History (UT Core)

Fall 

  • Varies CS Upper Division Elective #2

  • Varies Neuroscience Upper Division Elective #3

  • Varies Neuroscience Upper Division Elective #4

  • E 316L British Literature (UT Core)

Spring

  • Varies CS Upper Division Elective #3

  • Varies Neuroscience + CS CAPSTONE or research

  • GOV 312L or P Issues and Policies in American Government (UT Core)