Master of Engineering in Computation and Cognition

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The Department of Electrical Engineering and Computer Science and the Department of Brain and Cognitive Sciences offer a joint curriculum leading to a Master of Engineering (MEng) in Computation and Cognition that focuses on the emerging field of computational and engineering approaches to brain science, cognition and machine intelligence.

This program is only open to Computation and Cognition (6-9) majors at MIT and is best suited for students who wish to work towards a master’s degree but do not intend enroll in a doctoral program in a related field.

The curriculum provides flexibility to accommodate students with a wide diversity of interests in this area, from biologically-inspired approaches to artificial intelligence, to reverse engineering circuits in the brain. This joint master’s program prepares students for careers that include advanced applications of artificial intelligence and machine learning, as well as further graduate study in systems and cognitive neuroscience. Students in the program are full members of both departments.

The Master of Engineering in Computation and Cognition is a five- to five-and-a-half-year program in which Course 6-9 students earn a bachelors and master's degree. Students may earn the degree concurrently or sequentially with their undergraduate degree. Students will meet all degree requirements for the 6-9 major and complete an additional 90 units including 24 units of thesis work.  The MEng compresses the coursework necessary for a four-year bachelor's and a two-year master's degree into ten or eleven semesters. Students begin fulfilling MEng requirements in their latter semesters as undergraduates.

Admission Requirements

If you are a 6-9 major and your research program is adequately developed, you will be admitted into the MEng program if you meet these criteria:

  • A technical GPA 4.25 or better (letter grades in 6-9 courses and any other courses in 6, 8, or 18)
  • Completion of 9 subjects (or 102 units) counting toward the 6-9 major
  • An overall GPA of 4.0 is required by the end of the term in which students apply
  • One UROP or SuperUROP  (The EECS or BCS Office may contact research supervisors for their views on candidates).
  • A commitment from a faculty member to supervise their thesis research. Note: Non-MIT faculty such as postdocs, faculty at other universities and Institute research scientists can serve as co-advisors upon approval from the BCS Director of Education, but a MIT faculty advisor will still be needed. Purely engineering thesis projects will not be accepted.

Students in their junior year or first semester of senior year should submit an application in November or April. The application deadline is the last day of classes for that semester according to the MIT Academic Calendar. Decisions are typically sent out 2-3 weeks after the grade deadline as those grades will be considered in the application review process.

MEng Application Website (available in November and April; see application for deadline)

Degree Chart

The Master of Engineering degree is awarded only to students who have already received, or who will simultaneously receive, the Bachelor of Science in Computation and Cognition (Course 6-9). Refer to the undergraduate degree chart for requirements. 

The graduate component of the MEng program is described below.

Course 6-9P Graduate Requirements

Required Subjects  
6.THM Master of Engineering Program Thesis 24
Restricted Electives  
Four graduate subjects totaling at least 42 units, which includes two subjects from the EECS advanced subjects and two from the BCS advanced subjects 42-48
Two subjects from the list of mathematics restricted electives 24
Total Units 90-96

EECS Advanced Subjects

6.231 Dynamic Programming and Reinforcement Learning 12
6.241[J] Dynamic Systems and Control 12
6.245 Multivariable Control Systems 12
6.246, 6.247 Advanced Topics in Control 12
6.248, 6.249 Advanced Topics in Numerical Methods 12
6.251[J] Introduction to Mathematical Programming 12
6.252[J] Nonlinear Optimization 12
6.254 Game Theory with Engineering Applications 12
6.255[J] Optimization Methods 12
6.256[J] Algebraic Techniques and Semidefinite Optimization 12
6.260, 6.261 Advanced Topics in Communications 12
6.262 Discrete Stochastic Processes 12
6.263[J] Data-Communication Networks 12
6.265[J] Discrete Probability and Stochastic Processes 12
6.267 Heterogeneous Networks: Architecture, Transport, Proctocols, and Management 12
6.268 Network Science and Models 12
6.332, 6.333 Advanced Topics in Circuits 12
6.334 Power Electronics 12
6.335[J] Fast Methods for Partial Differential and Integral Equations 12
6.336[J] Introduction to Numerical Simulation 12
6.337[J] Introduction to Numerical Methods 12
6.338[J] Numerical Computing and Interactive Software 12
6.339[J] Numerical Methods for Partial Differential Equations 12
6.341 Discrete-Time Signal Processing 12
6.344 Digital Image Processing 12
6.345[J] Automatic Speech Recognition 12
6.347, 6.348 Advanced Topics in Signals and Systems 12
6.374 Analysis and Design of Digital Integrated Circuits 12
6.375 Complex Digital Systems Design 12
6.434[J] Statistics for Engineers and Scientists 12
6.435 Bayesian Modeling and Inference 12
6.436[J] Fundamentals of Probability 12
6.437 Inference and Information 12
6.438 Algorithms for Inference 12
6.440 Essential Coding Theory 12
6.441 Information Theory 12
6.442 Optical Networks 12
6.443[J] Quantum Information Science 12
6.450 Principles of Digital Communication 12
6.452 Principles of Wireless Communication 12
6.453 Quantum Optical Communication 12
6.454 Graduate Seminar in Area I 6
6.456 Array Processing 12
6.521[J] Cellular Neurophysiology and Computing 1 12
6.522[J] Quantitative Physiology: Organ Transport Systems 12
6.524[J] Molecular, Cellular, and Tissue Biomechanics 12
6.525[J] Medical Device Design 12
6.542[J] Laboratory on the Physiology, Acoustics, and Perception of Speech 12
6.544, 6.545 Advanced Topics in BioEECS 12
6.552[J] Signal Processing by the Auditory System: Perception 12
6.555[J] Biomedical Signal and Image Processing 12
6.556[J] Data Acquisition and Image Reconstruction in MRI 12
6.561[J] Fields, Forces, and Flows in Biological Systems 12
6.630 Electromagnetics 12
6.631 Optics and Photonics 12
6.632 Electromagnetic Wave Theory 12
6.637 Optical Imaging Devices, and Systems 12
6.644, 6.645 Advanced Topics in Applied Physics 12
6.685 Electric Machines 12
6.690 Introduction to Electric Power Systems 12
6.695[J] Engineering, Economics and Regulation of the Electric Power Sector 12
6.719 Nanoelectronics 12
6.720[J] Integrated Microelectronic Devices 12
6.728 Applied Quantum and Statistical Physics 12
6.730 Physics for Solid-State Applications 12
6.731 Semiconductor Optoelectronics: Theory and Design 12
6.732 Physics of Solids 12
6.735, 6.736 Advanced Topics in Materials, Devices, and Nanotechnology 12
6.774 Physics of Microfabrication: Front End Processing 12
6.776 High Speed Communication Circuits 12
6.777[J] Design and Fabrication of Microelectromechanical Systems 12
6.780[J] Control of Manufacturing Processes 12
6.781[J] Nanostructure Fabrication 12
6.820 Foundations of Program Analysis 12
6.823 Computer System Architecture 12
6.824 Distributed Computer Systems Engineering 12
6.828 Operating System Engineering 12
6.829 Computer Networks 12
6.830 Database Systems 12
6.832 Underactuated Robotics 12
6.833 The Human Intelligence Enterprise 12
6.834[J] Cognitive Robotics 12
6.835 Intelligent Multimodal User Interfaces 12
6.836 Multicore Programming 12
6.837 Computer Graphics 12
6.838 Shape Analysis 12
6.839 Advanced Computer Graphics 12
6.840[J] Theory of Computation 12
6.841[J] Advanced Complexity Theory 12
6.842 Randomness and Computation 12
6.845 Quantum Complexity Theory 12
6.846 Parallel Computing 12
6.849 Geometric Folding Algorithms: Linkages, Origami, Polyhedra 12
6.850 Geometric Computing 12
6.851 Advanced Data Structures 12
6.852[J] Distributed Algorithms 12
6.853 Topics in Algorithmic Game Theory 12
6.854[J] Advanced Algorithms 12
6.856[J] Randomized Algorithms 12
6.857 Network and Computer Security 12
6.858 Computer Systems Security 12
6.860[J] Statistical Learning Theory and Applications 12
6.863[J] Natural Language and the Computer Representation of Knowledge 12
6.864 Advanced Natural Language Processing 12
6.865 Advanced Computational Photography 12
6.866 Machine Vision 12
6.867 Machine Learning 12
6.869 Advances in Computer Vision 12
6.870 Advanced Topics in Computer Vision 12
6.872[J] Biomedical Computing 12
6.874[J] Computational Systems Biology: Deep Learning in the Life Sciences 12
6.875[J] Cryptography and Cryptanalysis 12
6.876 Advanced Topics in Cryptography 12
6.878[J] Advanced Computational Biology: Genomes, Networks, Evolution 12
6.881 Advanced Topics in Artificial Intelligence 12
6.882 Advanced Topics in Artificial Intelligence 12
6.883 Advanced Topics in Artificial Intelligence 12
6.884 Advanced Topics in Artificial Intelligence 12
6.885-6.888 Advanced Topics in Computer Systems 12
6.889-6.893 Advanced Topics in Theoretical Computer Science 12
6.894-6.896 Advanced Topics in Graphics and Human-Computer Interfaces 12
6.935[J] Financial Market Dynamics and Human Behavior 9
6.945 Large-scale Symbolic Systems 12
6.946[J] Classical Mechanics: A Computational Approach 12
1

Cannot count as EECS Advanced Subject if undergraduate version is taken as part of the Course 6-9 SB degree.

BCS Advanced Subjects

9.016[J] Acoustics, Production and Perception of Speech 12
9.021[J] Cellular Neurophysiology and Computing 1 12
9.073[J] Statistics for Neuroscience Research 2 12
9.110[J] Nonlinear Control 12
9.123[J] Neurotechnology in Action 12
9.181[J] Developmental Neurobiology 1 12
9.190 Computational Psycholinguistics 1 12
9.272[J] Topics in Neural Signal Processing 12
9.285[J] Audition: Neural Mechanisms, Perception and Cognition 12
9.301[J] Neural Plasticity in Learning and Memory 9
9.34[J] Biomechanics and Neural Control of Movement 12
9.422[J] Principles of Neuroengineering 12
9.455[J] Revolutionary Ventures: How to Invent and Deploy Transformative Technologies 9
9.520[J] Statistical Learning Theory and Applications 1 12
9.530 Emergent Computations Within Distributed Neural Circuits 1 12
9.583[J] Functional Magnetic Resonance Imaging: Data Acquisition and Analysis 12
9.601[J] Language Acquisition I 9
9.660 Computational Cognitive Science 1 12
9.822[J] Psychology and Economics 12
1

Cannot count as BCS Advanced Subject if undergraduate version is taken as part of the Course 6-9 SB degree.
2

Subject can count as BCS Advanced Subject or Mathematics Restricted Elective, but not both.

Mathematics Restricted Electives

Probability and Statistics (maximum of 1)  
Introduction to Inference 1  
Introduction to Probability 1  
Fundamentals of Probability  
Statistics for Brain and Cognitive Science 1  
Statistics for Neuroscience Research 2  
Topics in Neural Signal Processing 2  
Introduction to Probability and Statistics  
Probability and Random Variables  
Fundamentals of Statistics  
Discrete Mathematics (maximum of 1)  
Mathematics for Computer Science 1  
Principles of Discrete Applied Mathematics  
Linear Algebra (maximum of 1)  
Linear Algebra 1  
Modern Algebra  
Complex Variables (maximum of 1)  
Complex Variables with Applications  
Methods for Scientists and Engineers  
Real Analysis (maximum of 1)  
Real Analysis  
Other Subjects  
Statistical Physics I  
Computational Science and Engineering I  
Computational Science and Engineering II  
Introduction to Numerical Analysis  
Theory of Numbers  
1

Cannot count as Mathematics Restricted Elective if taken as part of the Course 6-9 SB degree.
2

Subject can count as BCS Advanced Subject or Mathematics Restricted Elective, but not both.
Funding

Departmental funding for the MEng program is not guaranteed. However, students may apply for funding from two sources: teaching assistantships and research assistantships. Students will have the opportunity to apply for funding before they begin the MEng program. Full-time TA or RA assistantships pay a monthly stipend, full tuition and health insurance. Students with TAships should expect to work approximately 20 hours a week on teaching. Students may request funding as a research assistant from their thesis supervisor, however, RA support for MEng students can be difficult to secure and advanced planning with research advisors is recommended.

Information regarding teaching assistantships in Course 6 including the application process can be found here. BCS does not typically have teaching assistantships to offer to MEng students.

Students with a full-time TAship or RAship may only register for two 12 unit subjects in addition to 12 units of thesis credit and 12 units of assistantship credit. Students holding a half TAship or half RAship may register for an additional class. Because students receive credit for their thesis work as well as TAships and RAships, they are registered for 48 to 60 units each term.

MEng students are only eligible for RAships and TAships during their first three regular semesters (summers are excepted) as a graduate student. If a student has been a graduate TA at least once or has unusual circumstances that have delayed progress on the thesis or classes, the student may request one additional term (a fourth term) of support eligibility.  

For more detailed information regarding the cost of attendance, including specific costs for tuition and fees, books and supplies, housing and food as well as transportation, please visit the SFS website.