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MEng: Electrical/Computer Engineering On-Campus

Electrical/computer engineering leverages the fundamental principles surrounding electricity to advance today’s emerging technologies ranging from semiconductor devices to advanced communication networks, from self-powered sensors to electric cars, from wearable devices to cognitive medical imaging, and from autonomous vehicles to smart cities.

Students may focus on a single specialization within electrical and computer engineering, or build an individualized curriculum from a combination of complementary subfields within the track.

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Course Requirements

The program consists of nine courses, of which five should be from the list of core courses. The remaining four electives can consist of any graduate-level engineering or science courses at Dartmouth.

Please note: The information below reflects degree requirements, effective as of Fall 2024.

COURSE TYPE	REQUIRED NUMBER OF COURSES	COURSES
Core Courses	5 courses	*Choose five (5) courses, all from one subfield:* Computer Engineering ENGS 93 or ENGG 193: Statistical Methods in Engineering ENGS 96: Math for Machine Learning ENGS 106: Principles of Machine Learning ENGG 107: Bayesian Statistical Modeling and Computation ENGS 108: Applied Machine Learning or COSC 274: Machine Learning and Statistical Data Analysis ENGS 112: Modern Information Technologies ENGS 128: Advanced Digital System Design COSC 55: Security and Privacy* COSC 258: Operating Systems COSC 269: Topics in Computer Systems COSC 278: Deep Learning Control, Signal Processing, and Image Processing ENGS 92: Fourier Transforms and Complex Variables ENGS 110: Signal Processing ENGS 111: Digital Image Processing ENGG 113: Image Visualization and Analysis ENGS 117: Computational Imaging ENGS 145: Modern Control Theory ENGS 147: Mechatronics ENGG 149: Introduction to Systems Identification ENGS 167: Medical Imaging ENGG 199.08: Post-Modern and Non-Linear Control Devices & Circuits ENGG 122: Advanced Topics in Semiconductor Devices ENGS 125: Power Electronics and Electromechanical Energy Conversion ENGS 126: Analog Integrated Circuits ENGS 127: Bioelectronics ENGS 129: Biomedical Circuits and Systems ENGS 131: Science of Solid State Materials ENGS 134: Nanotechnology ENGS 135: Thin Films and Microfabrication Technology ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering ENGS 162: Basic Biological Circuit Engineering ENGG 199.07: Introduction to Bioelectronics ENGS 262: Advanced Biological Circuit Engineering Optics & Electromagnetics ENGS 105: Computational Methods for Partial Differential Equations I ENGS 120: Electromagnetic Waves: Analytical and Modeling Approaches ENGS 123: Optics ENGS 124: Optical Devices and Systems ENGS 220: Electromagnetic Wave Theory PHYS 105: Electromagnetic Theory I Winter PHYS 106: Electromagnetic Theory II Spring Miniaturized & Mobile Health Sensors ENGS 108: Applied Machine Learning ENGS 125: Power Electronics and Electromechanical Energy Conversion ENGS 127: Bioelectronics ENGS 129: Biomedical Circuits and Systems ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering ENGS 169: Intermediate Biomedical Engineering * MEng students selecting this course will be required to gain permission of the instructor and be assigned additional coursework in order to receive graduate credit.
Electives	4 courses	*Choose four (4) courses, from the following:* Engineering Any graduate-level engineering sciences course. Design Project Students may take one of the following options to partially fulfill the four-course elective requirement. The appropriate option will depend on each student’s prior experience and coursework since the two tracks require different prerequisites. Option 1 (1 course) ENGM 191: Product Design and Development Option 2 (2 courses) ENGS 190: Engineering Design and Methodology Project Initiation ENGS 290: Engineering Design Methodology and Project Completion Science Any graduate-level science course.

COURSE TYPE

REQUIRED NUMBER OF COURSES

COURSES

Core Courses

5 courses

Choose five (5) courses, all from one subfield:

Computer Engineering
ENGS 93 or ENGG 193: Statistical Methods in Engineering
ENGS 96: Math for Machine Learning
ENGS 106: Principles of Machine Learning
ENGG 107: Bayesian Statistical Modeling and Computation
ENGS 108: Applied Machine Learning or COSC 274: Machine Learning and Statistical Data Analysis
ENGS 112: Modern Information Technologies
ENGS 128: Advanced Digital System Design
COSC 55: Security and Privacy*
COSC 258: Operating Systems
COSC 269: Topics in Computer Systems
COSC 278: Deep Learning

Control, Signal Processing, and Image Processing
ENGS 92: Fourier Transforms and Complex Variables
ENGS 110: Signal Processing
ENGS 111: Digital Image Processing
ENGG 113: Image Visualization and Analysis
ENGS 117: Computational Imaging
ENGS 145: Modern Control Theory
ENGS 147: Mechatronics
ENGG 149: Introduction to Systems Identification
ENGS 167: Medical Imaging
ENGG 199.08: Post-Modern and Non-Linear Control

Devices & Circuits
ENGG 122: Advanced Topics in Semiconductor Devices
ENGS 125: Power Electronics and Electromechanical Energy Conversion
ENGS 126: Analog Integrated Circuits
ENGS 127: Bioelectronics
ENGS 129: Biomedical Circuits and Systems
ENGS 131: Science of Solid State Materials
ENGS 134: Nanotechnology
ENGS 135: Thin Films and Microfabrication Technology
ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering
ENGS 162: Basic Biological Circuit Engineering
ENGG 199.07: Introduction to Bioelectronics
ENGS 262: Advanced Biological Circuit Engineering

Optics & Electromagnetics
ENGS 105: Computational Methods for Partial Differential Equations I
ENGS 120: Electromagnetic Waves: Analytical and Modeling Approaches
ENGS 123: Optics
ENGS 124: Optical Devices and Systems
ENGS 220: Electromagnetic Wave Theory
PHYS 105: Electromagnetic Theory I Winter
PHYS 106: Electromagnetic Theory II Spring

Miniaturized & Mobile Health Sensors
ENGS 108: Applied Machine Learning
ENGS 125: Power Electronics and Electromechanical Energy Conversion
ENGS 127: Bioelectronics
ENGS 129: Biomedical Circuits and Systems
ENGS 159: Molecular Sensors & Nanodevices in Biomedical Engineering
ENGS 169: Intermediate Biomedical Engineering

* MEng students selecting this course will be required to gain permission of the instructor and be assigned additional coursework in order to receive graduate credit.

Electives

4 courses

Choose four (4) courses, from the following:

Engineering**
Any graduate-level engineering sciences course.

Design Project
Students may take one of the following options to partially fulfill the four-course elective requirement. The appropriate option will depend on each student’s prior experience and coursework since the two tracks require different prerequisites.

Option 1 (1 course)

ENGM 191: Product Design and Development

Option 2 (2 courses)

ENGS 190: Engineering Design and Methodology Project Initiation
ENGS 290: Engineering Design Methodology and Project Completion

Science**
Any graduate-level science course.

** Students may choose electives from any graduate-level engineering or science courses offered at Dartmouth. The courses listed here are for recommended students who seek additional further depth of study in their chosen track. With the exception of ENGM 191: Product Design and Development, MEng students may not take ENGM courses for credit.