Program Overview

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Overview

The interdisciplinary BS/MS program in Neural Engineering delivers a rigorous training and the necessary skills required to solve complex problems at the interface of engineering, medicine, and neuroscience. Graduates are prepared for successful careers in the biomedical industries, academia, or government (FDA, US Patent Office), or for further study in doctoral or health-related programs.

Admission Requirements

The BS/MS program in Neural Engineering welcomes students from diverse backgrounds, including:

• Students enrolled in UM undergraduate degrees in biomedical engineering and other engineering disciplines who seek advanced professional training or specialization in a particular area of neural engineering;
• Students enrolled in UM undergraduate programs in Physics, Mathematics, Neuroscience, Computer Science, Chemistry, Biology, or other fields of natural or health science who seek to diversify their career opportunities by acquiring an engineering degree;
• Students preparing for admission to advanced health-related or other professional programs such as medical school.

When to apply: For BS/MS: Qualified students must apply prior to the advising period but at the latest before the final exams in the second semester of their junior year. Students are strongly advised to apply to the BS/MS program as early as possible in their junior year to facilitate academic advising and course selection in the second semester of their junior year. Before submitting an application, interested students should discuss the program and the possibility of entering the program with an academic advisor.

Curriculum Requirements

The graduate component of the BS/MS in Neural Engineering curriculum consists of three components: core courses, elective courses on neural engineering, and an industry or capstone project. Students must complete at least 30 credits of graduate-level courses to complete the degree.

Core Courses

The core courses teach the fundamental skills of neuroscience, neuroanatomy, and physiology.

Elective Courses

The interdisciplinary electives in neural engineering courses are designed to fit the student’s chosen competency in specific areas of neural engineering supported by the program.

Industry or Capstone Project

The industry or capstone project will be taken for 6 credits. Projects are done typically within two semesters, supervised by a faculty member in an appropriate academic unit within the program (Biomedical Engineering, Computer Science, Neuroscience, Biology, Physics, Physiology and Biophysics, Psychology, or Electrical Engineering). Students can also complete their projects in an industry-setting. The project culminates with a report (or a research manuscript) detailing the milestones achieved/work completed and knowledge gained, and a presentation to faculty and students in the program.

Curriculum Requirements

Course List Code | Title | Credit Hours
---|---|---
BACHELOR'S DEGREE REQUIREMENTS| 120
MASTER'S DEGREE REQUIREMENTS|
Core Courses|
BME 615| Current Trends in Neural Engineering| 3
Graduate Level Neuroscience Course chosen from the following:| 3
BME 603| Neurophysiology for Engineers|
NEU 762| NEU II - Systems Neuroscience|
NEU 797| Neuroanatomy|
PHS 741| Principles of Membrane Physiology and Biophysics I|
Statistics Course Chosen from the Following:| 3
PIB 705| Biostatistics for the Biosciences|
ECE 730| Statistical Learning|
MTH 642| Statistical Analysis|
MTH 625| Introduction to Mathematical Statistics|
BST 605| Statistical Principles of Clinical Trials|
BIL 618| Advanced Biostatistics|
Neural Engineering Interdisciplinary Electives| 15
To be selected from the following any graduate level courses for the neural engineering track (some courses may have pre-requisites that must be met prior to enrollment):|
CSC 646| Machine Learning|
CSC 649| Biomedical Data Science|
CSC 650| Computational Neuroscience|
BIL 668| Developmental Neuroscience|
BME 735| Auditory and Visual Neural Systems|
BME 612| Regulatory Control of Biomedical Devices|
BME 695| Current Trends in Regenerative Medicine|
BME 635| Advanced Biomaterials|
BME 640| Microcomputer-Based Medical Instrumentation|
BME 624| Neuromotor Engineering|
BME 610| Introduction to Medical Robotics|
ECE 753| Pattern Recognition and Neural Networks|
ECE 637| Principles of Artificial Intelligence|
ECE 648| Machine Learning|
ECE 677| Data Mining|
CSC 645| Advanced Artificial Intelligence|
CSC 746| Neural Networks and Deep Learning|
MTH 613| Partial Differential Equations I|
MTH 614| Partial Differential Equations II|
MTH 615| Ordinary Differential Equations|
MTH 621| Numerical Methods in Differential Equations|
NEU 762| NEU II - Systems Neuroscience|
NEU 797| Neuroanatomy|
PHS 741| Principles of Membrane Physiology and Biophysics I|
Project| 6
BME 725| Special Problems|
Industry Project|
This can be a three-summer month or six-month (equivalent of 2 semesters) industry project. The project will culminate with a report detailing the work done and knowledge gained, and a presentation to faculty and students in the program.|
Capstone Project|
To complete the project, the student will have at least one supervisor within an appropriate academic unit in the program. Prior to initiating the thesis project, approvals from the academic advisor and BME department chair are required.|
BME / Miami Project / NEU Seminars| 0
Students must attend at least 9 seminars in topics on neural engineering and neuroscience at the University.|
Total Credit Hours| 150

Sample Plan of Study (5 Years)

BS in Computer Science/MS in Neural Engineering

Plan of Study Grid Freshman Year

Fall| Credit Hours
Undergraduate Courses | 15
| Credit Hours| 15
Spring
Undergraduate Courses | 15
| Credit Hours| 15
Sophomore Year
Fall
Undergraduate Courses | 15
| Credit Hours| 15
Spring
Undergraduate Courses | 15
| Credit Hours| 15
Junior Year
Fall
Undergraduate Courses | 18
| Credit Hours| 18
Spring
Undergraduate Courses | 18
| Credit Hours| 18
Senior Year
Fall
Undergraduate Courses | 12
CSC 646 | Machine Learning | 3
BME 603 | Neurophysiology for Engineers | 3
| Credit Hours| 18
Spring
Undergraduate Courses | 12
CSC 650 | Computational Neuroscience | 3
BME 615 | Current Trends in Neural Engineering | 3
| Credit Hours| 18
Fifth Year (Graduate)
Fall
BME 640 | Microcomputer-Based Medical Instrumentation | 3
CSC 746 | Neural Networks and Deep Learning | 3
BME 725 | Special Problems | 3
| Credit Hours| 9
Spring
BME 612 | Regulatory Control of Biomedical Devices | 3
ECE 753 | Pattern Recognition and Neural Networks | 3
BME 725 | Special Problems | 3
| Credit Hours| 9
| Total Credit Hours| 150

BS in Neuroscience/MS in Neural Engineering

Plan of Study Grid Freshman Year

Fall| Credit Hours
Undergraduate Courses | 15
| Credit Hours| 15
Spring
Undergraduate Courses | 15
| Credit Hours| 15
Sophomore Year
Fall
Undergraduate Courses | 15
| Credit Hours| 15
Spring
Undergraduate Courses | 15
| Credit Hours| 15
Junior Year
Fall
Undergraduate Courses | 18
| Credit Hours| 18
Spring
Undergraduate Courses | 18
| Credit Hours| 18
Senior Year
Fall
Undergraduate Courses | 12
CSC 646 | Machine Learning | 3
BME 615 | Current Trends in Neural Engineering | 3
| Credit Hours| 18
Spring
Undergraduate Courses | 12
CSC 650 | Computational Neuroscience | 3
BME 624 | Neuromotor Engineering | 3
| Credit Hours| 18
Fifth Year (Graduate)
Fall
CSC 746 | Neural Networks and Deep Learning | 3
NEU 762 | NEU II - Systems Neuroscience | 4
BME 725 | Special Problems | 3
| Credit Hours| 10
Spring
BME 612 | Regulatory Control of Biomedical Devices | 3
BME 695 | Current Trends in Regenerative Medicine | 3
BME 725 | Special Problems | 3
| Credit Hours| 9
| Total Credit Hours| 151

BS in Biomedical Engineering/MS in Neural Engineering

Plan of Study Grid Freshman Year

Fall| Credit Hours
Undergraduate Courses | 15
| Credit Hours| 15
Spring
Undergraduate Courses | 15
| Credit Hours| 15
Sophomore Year
Fall
Undergraduate Courses | 15
| Credit Hours| 15
Spring
Undergraduate Courses | 15
| Credit Hours| 15
Junior Year
Fall
Undergraduate Courses | 18
| Credit Hours| 18
Spring
Undergraduate Courses | 18
| Credit Hours| 18
Senior Year
Fall
Undergraduate Courses | 12
BME 603 | Neurophysiology for Engineers | 3
CSC 646 | Machine Learning | 3
| Credit Hours| 18
Spring
Undergraduate Courses | 12
BME 612 | Regulatory Control of Biomedical Devices | 3
BME 615 | Current Trends in Neural Engineering | 3
| Credit Hours| 18
Fifth Year (Graduate)
Fall
BME 640 | Microcomputer-Based Medical Instrumentation | 3
CSC 746 | Neural Networks and Deep Learning | 3
BME 725 | Special Problems | 3
| Credit Hours| 9
Spring
BME 635 | Advanced Biomaterials | 3
PHS 741 | Principles of Membrane Physiology and Biophysics I | 2
BME 725 | Special Problems | 3
Additional Elective | 1
| Credit Hours| 9
| Total Credit Hours| 150

The MS program in Neural Engineering provides competency in one of the three areas:

• Neurostimulation
• Neurorehabilitation
• Regenerative medicine

Curriculum setup: Students admitted in the dual degree BS/MS program can take a maximum of six (6) graduate credits per semester in their senior year, for a maximum of twelve (12) graduate credits per year, without incurring additional costs if they are full-time undergraduate students during this period. Graduate technical electives taken in the senior year must be chosen with the approval of their academic advisor. The credits of graduate technical electives completed in the fourth year are counted toward the 30 credits required for the MS degree. In the fifth year, BS/MS students complete the rest of their 18 credits of graduate course requirements, including completion of the MS Project.

Pre-requisites: Applicants for BS/MS may be enrolled in any undergraduate major. However, they will be expected to have taken and passed a course each (or equivalent training) in Statistics and Probability, and Programming.