Information for Prospective M.Eng. Students

Admission Timeline Costs and Financial Aid Frequently Asked Questions

Admission

Who Should Apply

The Master of Engineering (M.Eng.) is designed for students who plan to join the engineering profession following graduation. The accelerated program is designed to develop professional engineering leaders of the future who understand the technical, economic, and social issues of technology. More information about this degree program can be found at the M.Eng. Program Description and the College of Engineering Fung Institute websites. Students planning to pursue a PhD degree should consider the Master of Science (M.S.) degree.

Application Requirements

admchecklist

Please consult the M.Eng. Admissions Checklist for complete admissions requirements.

The application deadline was January 6, 2016. Admissions decisions will be announced in early March by e-mail.

The Fall 2016 Admissions Application will open in early September 2015.


Suggestions for Applicants Without a CS Degree

Although we do not require applicants to our computer science programs to have a degree in computer science, we do expect them to have a strong technical background equivalent to a computer science bachelors degree. Admission to these programs requires experience in programming, algorithms, data structures, and theory at or above the undergraduate level.

Info Sessions

For the MEng program, the Fung Institute holds online info sessions. Learn more and register

Contact Us

Email: gradadmissions at eecs.berkeley.edu

Program Requirements by Area

  Data Science and Systems

All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute's engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department.

2015-2016 Capstone Projects

For the capstone projects for Master of Engineering in Electrical Engineering and Computer Science (EECS) our department believes that the students are going to have a significantly better experience if the projects are followed closely by an EECS professor throughout the academic year. To ensure this, we have asked the faculty in each area for which the Master of Engineering is offered in our department to formulate one or more project ideas that the incoming students will have to choose from. We list below the titles and faculty advisor for these capstone choices in the area. Depending on the number of enrolled students in the area, we may run only a subset of these project ideas.

Project 1 Title - Graphic Tools for big data (advisor Prof. John Canny)
Description - Implement new *interactive* browser-based visualization tools for big data. Big Data workflows often require extensive "tuning": model parameters must be adjusted and tradeoffs must be made between different performance metrics. The best-performing models are also seldom "pure" and involve mixtures of base models, sometimes dozens or even hundreds. All of these cases involve close interaction between the system and a data scientist. The goal of this project is to build tools that allow the data scientist to not only see what is going on but to intervene and interact with live models.
Project 2 Title - Streaming model synchronization for deep learning and more (advisor Prof. John Canny)
Description - Port near-optimal streaming "allreduce" primitives to popular cluster frameworks including Apache Storm and Yarn. Currently the data produced by high-performance machine learning systems strains the network communication primitives that are available (map-reduce reduce, or tree reduce or MPI). Because of network bottlenecks, the fastest implementations of many machine learning algorithms are on single machines. The goal of this project is to speed up common communication patterns (allreduce) on clusters using layered, low-degree primitives. A recent rooflined network primitive called "Kylix" set the record for distributed pagerank (which is an allreduce problem). The goal of this project is to port and generalize Kylix to popular cluster frameworks such as Apache Storm and Yarn.
Project 3 Title - Development of Entrepreneurial Opportunities in Patent Data Analysis (advisor Prof. Lee Fleming)
Description - World wide patent data are now available for a variety of commercially interesting analyses, including patent valuation, the prediction of prosecution success, and the probability of litigation. This Capstone project will first survey the commercial landscape, identify opportunities, and then develop the intellectual capital that could enable the launch of a startup and/or licensing of UC Berkeley technology. Technical challenges will include machine learning techniques (such as classifiers for disambiguation), natural language processing (to extract salient facts from legal documents), and blockmodeling techniques (to reduce millions of patent prosecution histories to an interpretable graph).

Technical Courses

At least two of your four technical courses should be chosen from the list below. The remaining technical courses should be chosen from your own or another MEng area of concentration within the EECS Department.

Fall 2015

Spring 2016

Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.

  Physical Electronics and Integrated Circuits

All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute's engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department.

The Physical Electronics and Integrated Circuits areas have been combined due to the many commonalities between them. Students in either area may choose from a combined set of capstone projects and technical courses as shown below.

2015-2016 Capstone Projects


For the capstone projects for Master of Engineering in Electrical Engineering and Computer Science (EECS) our department believes that the students are going to have a significantly better experience if the projects are followed closely by an EECS professor throughout the academic year. To ensure this, we have asked the faculty in each area for which the Master of Engineering is offered in our department to formulate one or more project ideas that the incoming students will have to choose from. We list below the titles and faculty advisor for these capstone choices in the area. Depending on the number of enrolled students in the area, we may run only a subset of these project ideas.

Project 1 Title - Petabit switch-fabric design (advisors Prof Vladimir Stojanovic and Elad Alon)
Description - In this project the team will explore the circuits and architectures for building a 1000-port switch-fabric with petabit bisection bandwidth, for emerging cloud-computing applications. The fabric will consist of high-speed electrical or photonic SerDes I/O and a variety of crossbar architectures. The project will build-up the high-speed digital and analog/mixed-signal design skills as well as exposure to silicon-photonics and switch architectures.
Project 2 Title - Digital Radio Baseband and Testbed for Next Generation Wireless System (advisors Profs. Borivoje Nikolic and Vladimir Stojanovic)
Description - In this project the team will set-up the hardware infrastructure for next-generation mm-wave indoor radio link. The infrastructure will consist of physical layer baseband processing algorithms (carrier-timing recovery, modulation, coding, synchronization, etc) mapped onto FPGA flow and setting-up a full communication path to the transmitter and receiver arrays. The project will build-up the digital design and communication system implementation skills as well as exposure to high-speed ADC/DACs and mm-Wave radios.
Project 3 Title - Beamforming and MIMO Digital Radio Baseband and Testbed for Next Generation Wireless System (advisors Profs. Elad Alon and Vladimir Stojanovic)
Description - In this project the team will set-up the hardware infrastructure for next-generation mm-wave beamforming/MIMO indoor wireless network. The infrastructure will consist of physical layer baseband processing algorithms (beamforming, Massive MIMO) mapped onto FPGA flow and setting-up a full communication path to the transmitter and receiver arrays. The project will build-up the digital design and communication system implementation skills as well as exposure to high-speed ADC/DACs and mm-Wave radios.

Technical Courses

Fall 2015

Spring 2016


Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.

  Robotics and Embedded Software

Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute's engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department.

2015-2016 Capstone Projects

For the capstone projects for Master of Engineering in Electrical Engineering and Computer Science (EECS) our department believes that the students are going to have a significantly better experience if the projects are followed closely by an EECS professor throughout the academic year. To ensure this, we have asked the faculty in each area for which the Master of Engineering is offered in our department to formulate one or more project ideas that the incoming students will have to choose from. We list below the titles and faculty advisor for these capstone choices in the area. Depending on the number of enrolled students in the area, we may run only a subset of these project ideas.

Project 1 Title - Wireless technology for collecting information from families on the verge of poverty (advisors Profs. Ruzena Bajcsy and Mauricio Miller and his technical personnel from fii.org)
Description - In collaboration with the Organization of Family Independence Initiative (FII.org) the CEO Mauricio Miller, who have a data base of 1,000 families across the USA, we recognized the need to facilitate these families with wireless technologies in order to monitor their social patterns of movements, connections with their peers/families, shopping patterns, health care and educational needs. The technical challenges are as follows: 1. There is a need to have flexible interface of several different mobile platforms with servers in order to collect the geographical patterns of their movements, and health signs of individual while respecting their privacy. 2. There is a need to reconcile the textual information that already exists in their database with the signal measurements that comes from the mobile devices. 3. There is a need to identify features that clusters different people so that we can use these connections for positive reinforcement of these groups to improve their lives.
Project 2 Title - Interactive remote Diagnostics of physically handicapped patients (advisor Prof. Ruzena Bajcsy, Gregorij Kurillo, and Dr. Jay Han)
Description - At UCB we have developed a Kinect (3D camera) base system, installed simultaneously in two remote places (we have demonstrated its feasibility between Spain and Berkeley, USA) that can transmit in real time video, 3D information and audio in both directions. This technology offers a possibility to perform medical diagnosis for the physician and patient not being in the same place. While we have shown the feasibility of this system, some serious studies of the usability are in order. On the technical level we need to study the effect on the communication with respect to the quality of the signal transmitted (spatial, and temporal resolution, the effect of noise, loosing packets through the network and the delay due to the network). Another aspect to study is the tradeoff between the amount of data transmitted and the amount of computation deployed, such as interpolation and extrapolation, use of a prior models on the subjects. Finally asses under what medical conditions such a video/audio communication suffices vs. face to face communication.
Project 3 Title - Sensory Fusion and Selection for Car and its driver with respect to the safe driving (advisor Prof. Ruzena Bajcsy and Katherine Driggs Campbell)
Description - We are in possession of a sophisticated Car simulator with capabilities of testing driver's ability to drive under varied road conditions. We can measure all the necessary car state/input variables (velocity, acceleration and braking, steering angles) but also to some degree the road conditions (inhomogeneity of the surface road). In addition we can measure the driver's head, shoulder, eye movements to assess how much they pay attention to the driving conditions. We also have motion capture capabilities that can simulate the outer sensors on the car which now many of the higher cost cars have The proposed Capstone project is to: 1. Model each sensors its range, spatiotemporal resolution, sensitivity, signal/noise ratio. 2. Add to the current sensors suit EMG sensor on the leg and evaluate its capacity to detect the forces during the acceleration and/or braking for individual subject. 3. Given the sensor suit and their models design a selection algorithm for different sensor or a subset of sensors depending on the road situations which will optimize the information obtained with respect to the safety on the road. 4. If time permits, add Visual signal for Car to car communication.
Project 4 Title - Application of Collaborative Robots to Two-Person Manipulation Tasks (advisor Prof. Ruzena Bajcsy and Aaron Bestick)
Description - Many tasks which could be performed by service, personal, and industrial robots would traditionally require two people to accomplish. Examples include making a bed, assembling large pieces of furniture, placing large pieces of sheet metal, drywall or other building materials, and a huge variety of other tasks. A variety of programming by demonstration (PbD) algorithms allow a single robot to learn how to perform a task based on a collection of human demonstrations. However, collaborative tasks performed by more than one person can introduce a number of unique challenges for PbD. A key problem is that many PbD algorithms do not explicitly model the motion constraints imposed by the size, shape, and flexibility of the object being manipulated. For this project, you will choose a two-person manipulation task that you'd like to train a pair of robots to accomplish. You'll collect demonstrations of humans performing the task, and apply a PbD approach to both train the robot to accomplish the task autonomously, and to explicitly model kinematic constraints imposed on the robots' motion by the object and incorporate these into the robots' motion planning. Tools available: Two Baxter robots (two arms each, cameras, joint torque sensing), One UR5 robot arm, PhaseSpace motion capture system, Other standalone sensors (IMUs, force/torque, etc.)

Technical Courses

Fall 2015

Spring 2016

Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.

  Signal Processing and Communications

Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute's engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department.

2015-2016 Capstone Projects

For the capstone projects for Master of Engineering in Electrical Engineering and Computer Science (EECS) our department believes that the students are going to have a significantly better experience if the projects are followed closely by an EECS professor throughout the academic year. To ensure this, we have asked the faculty in each area for which the Master of Engineering is offered in our department to formulate one or more project ideas that the incoming students will have to choose from. We list below the titles and faculty advisor for these capstone choices in the area. Depending on the number of enrolled students in the area, we may run only a subset of these project ideas.

Project 1 Title - Scalable video-on-demand with edge resources (advisor Prof. Kannan Ramchandran)
Description - In our research group at Berkeley, we have recently developed an exciting new platform (theory and algorithms) for delivering Video-on-Demand (VoD) content in a highly scalable, robust, and distributed way with the aid of peer cooperation. Our approach is based on massively aggregating the "micro-resources" of storage, CPU, bandwidth, and connectivity available at peer edge devices like laptops and tablets. We have come up with the theory and a fully distributed algorithm that figures out how each edge device should interact with the rest of the system in such a way that everyone's resources are maximally utilized.

As a concrete application of this framework, imagine being able to deliver ultra-high-def (UHD) video quality having 16x the resolution of HD video, without any investment in additional infrastructure by seamlessly leveraging the available "spare" resources at the edges. Imagine a platform that can deliver UHD video at the same cost that you pay for Netflix today: isn't that cool? While we have developed the theory and algorithm, and observed its huge potential, much work remains to make it viable and practical. We would like to push this project forward into a real deployable system and change the way that video is delivered and watched in the near future.
Project 2 Title - (Simulating) Spectrum Access Systems (advisor Prof. Anant Sahai)
Description - The wireless world is at the brink of a revolution. Traditionally, radio spectrum was statically cut into different bands that were then allocated to different uses, and within any band, channels were assigned to individual entities (like AT&T, Verizon, Sprint, etc.). This was done for a practical reason --- to limit radio interference. One set of bands, the unlicensed bands, is special in that everyone is allowed to use them, and devices are individually responsible for managing interference. Crudely speaking, the traditional static approach corresponds to having dedicated wires while the traditional unlicensed approach corresponds to purely packet-based networking. The advance of information technology and the congestion of radio spectrum have brought us to a point where we need to basically bring software defined networking (SDN) ideas to radio spectrum. Instead of having static allocations (done by lawyers), we will have Spectrum Access Systems (SAS) that manage wireless use across different systems. This involves bringing in modern techniques involving databases, wireless signal processing, learning, security, mechanism-design, and networking. It also touches on law and economics. Because SASs change the competitive landscape, they also create all sorts of interesting business-model questions that need to be explored. To support this exploration, we envision in this project to work towards building a toy SAS simulator building on our existing Python research codebase. The exact direction that the project will take will depend on the interests of the students who join it.

Technical Courses

Fall 2015

Spring 2016

Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.

  Visual Computing and Computer Graphics

Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the EECS department at the graduate level, the Fung Institute's engineering leadership curriculum, as well as a capstone project that will be hosted by the EECS department.

2015-2016 Capstone Projects

For the capstone projects for Master of Engineering in Electrical Engineering and Computer Science (EECS) our department believes that the students are going to have a significantly better experience if the projects are followed closely by an EECS professor throughout the academic year. To ensure this, we have asked the faculty in each area for which the Master of Engineering is offered in our department to formulate one or more project ideas that the incoming students will have to choose from. We list below the titles and faculty advisor for these capstone choices in the area. Depending on the number of enrolled students in the area, we may run only a subset of these project ideas.

Project 1 Title - FabSense (advisor Prof. Eric Paulos)
Description - Empower everyday shop and hand tools to be in conversation with the emerging landscape of digital fabrication hardware Keywords: Machine Learning, Python, Inertial Measurement Unit, Fabrication

The push for computational fabrication has left the important landscape of our everyday hand tools from working in concert and conversation with the world of digital fabrication. How can smart, low-cost, non-invasive sensing, and advances in computation be seamlessly integrated to provide a more reflective, interactive, and powerful making ecosystem. We feel there is a growing need to empower everyday shop and hand tools to be in conversation with the emerging landscape of digital fabrication hardware. Our plan is to use finger worn sensors to assist in tutorial construction, training, and verification of hands-on construction tasks. Making is a process filled with not just fabrication equipment and digital technologies but a wealth of hand tools and very analog actions. We envision tremendous value in designing experiences and interfaces around the these hand tools that enriches their experience, increases their value to the making process, and beings them into conversation with digital fabrication tools all while maintaining the important characteristics of their analog nature.
Project 2 Title - Flixels (advisor Prof. Eric Paulos)
Description - Flixels are coordinated swarms of quadcopters with programable lights. As flying pixels, they collectively form airborne, scalable, dynamic, interactive, deformable, sensing, displays. They can be programmed to communicate messages, respond to sensed data (i.e. traffic, air quality, fault lines, underground subways, etc), redirect and navigate people, form conceptualized physical building outlines within cities, participate in gameplay with people (i.e. keeping score, de-marking boundaries, and augmenting field and street games with lights and sounds), be a novel kinetic visual expressive medium, interact with people (i.e. react as waves or particles when people gesture against them), and empower communities to message and 'tag' public and private spaces in real-time. Through a novel interface, swarms of quadcopters can be programmed to perform, sense, or respond. Flixels leverage advanced robotic path planning, computer graphics, vision, and animation techniques to create an extremely novel, visually expressive system for public use. Flixels can form 'displays' of any shape or curvature and exploit motion as visual and communication elements. They allow unique imagery from different viewpoints. While battery life is still a limiting factor, flying 25+ quadcopters for 10-30 minutes are achievable ranges for exploring and experiencing the fascinating and expressive landscape of Flixels. With additional robotic planning this limit can be extended, broadening the scope and design landscape for Flixels.

Project 3 Title - Bio-Electric Hybrids (advisor Prof. Eric Paulos)
Description - This project is focused on the intersection of three fundamental emerging movements within the culture of technology: mobile platforms, sensing, and biology. More specifically, we propose to study, design, and develop, a new area of mobile sensing using biomarkers as sensor input. While we envision a broad range of applications, the initial driving platform is citizen science. Mobile phones provide a flexible, networked, user interface. Both in our own work and that or others, novel sensing has been proposed and developed for a range of inferencing and citizen science contexts. We claim that recent developments in the use of novel, low-cost biological materials and methods for sensing are significant and important new research areas for HCI. One challenge is in the design and integration of these biomarkers into electronic digital systems. In this proposal we will initiate and develop fundamental research into this hybrid space of low-cost personal bio-sensors integrated into mobile systems.
Project 4 Title - Programmable Materials: Magnetic Sketching (advisor Prof. Eric Paulos)
Description - Interactive experiences have be rapidly moving off of our desktop and onto our laps (pads), hands (smartphones), wrists, (smartwatches), and walls (smartboards). While each of these unique form factors bring with them new challenges and opportunities for designers, the interaction metaphors and existing prototyping tools remain largely derivative of prior static, screen-based themes. In this project we explore Magnetic Sketching as a new technique for rapidly exploring kinetic interactive designs using a broad new range of novel materials. We can magnetically actuate non-ferrous materials by infusing them with ferrofluid or iron filings, which are both low-cost and readily available chemicals. This novel and accessible design method enables designers to freely explore and sketch unique material motions and behaviors. With this technique, these typically non-magnetic materials can be moved without additional components, wires, interconnects, or heating. Finally, we highlight a range of designerly inspired potential applications through a series of examples and discuss future usage.
Project 5 Title - Sensr: Citizen Science for All (advisor Prof. Eric Paulos)
Description - Build, deploy, and study a range of novel, accurate air quality technologies within specific community groups and stakeholders to inspire 'new ways of seeing' understanding, interpreting, and taking action to improve our world through novel technology, community engagement, sensing platforms, and crowd sourcing tools. Provide new cooperative and collaborative approaches to problem solving across a variety of expert practitioners including environmental, computer, and social scientists, atmospheric chemists, environmental health organizations such as the EPA, urban planners, local/national governments, & nonprofits. This work focuses on the development of a new citizen science campaign authoring app.
Project 6 Title - Vision Correcting Displays (advisor Prof. Brian A. Barsky)
Description - Vision problems such as near-sightedness, far-sightedness, as well as others, are due to optical aberrations in the human eye. These conditions are prevalent, and the number of people who have these hardships is growing rapidly. Correcting optical aberrations in the human eye is traditionally done optically using eyeglasses, contact lenses, or refractive surgeries; these are sometime not convenient or not always available to everyone. Furthermore, higher order aberrations are not correctable with eyeglasses.
This research is investigating a novel approach which involves a new computation based aberration-correcting light field display: by incorporating the person's own optical aberrations into the computation, content shown on the display is modified such that the viewer will be able to see the display in sharp focus without using corrective eyewear. Our research involves the analysis of image formation models; through the retinal light field projection, it is possible to compensate for the optical blurring on the target image by a process of prefiltering with the inverse blur. As part of this project, we are building a light field display prototype that supports our desired inverse light field prefiltering. We are working towards extending the capability to correct for higher order aberrations. This latter aspect is particularly exciting since it would enable people for whom it is not possible to see displays in sharp focus using eyeglasses to be able to do so using no corrective eyewear.
Project 7 Title - A social/mobile platform for optimizing health services for complex, chronic care management (advisor Prof. Bjoern Hartman)
Description - There is national concern about the cost, quality, and access to healthcare in the current environment of the Affordable Care Act and other healthcare reforms. Among these concerns is the prevalence of complex chronic diseases such as diabetes, heart disease, and cancer in the population in general, and the higher prevalence in low income and minority populations served in community health centers. The purpose of this project is to develop a working prototype of a social/mobile platform for adaptive care coordination for complex health conditions that can enable collaboration between patients with care teams. We will apply a participatory design and agile development-informed methodology to create a prototype of this platform with 12-16 clinicians, patients, caregivers, and health workers.

Technical Courses

Fall 2015

Spring 2016

Note: The courses listed here are not guaranteed to be offered, and the course schedule may change without notice. Refer to the UC Berkeley Course Schedule for further enrollment information.

Timeline

Various Times and Locations Info Sessions through the Fung Institute Register Here
September 2015 (TBD) Info Session with EECS Department
January 6, 2016 11:59pm Online Application and Supplemental Materials Deadline
January - February 2016 Interviews (only if admissions committee has additional questions)
March 2016 Admissions Decisions, Via email
April 15, 2016 Statement of Intent to Register Deadline
June 2016 Capstone Project Matching, emails through EECS
August 2016 Mandatory Orientations, UC Berkeley Campus
August 2016 Classes Begin

Costs and Financial Aid

Tuition & Fees

Tuition and fees for the Master of Engineering program 2015-2016 academic year are estimated to be $48,693.50 for CA Residents and $52,298.50 for Nonresidents. Final fees for some non-tuition items such as Health Insurance are not finalized until June. Total billable costs may be slightly higher.

To check the most up-to-date fee information at any time, visit the Office of the Registrar. (Fees on the Office of the Registrar website are shown per semester, and currently contain the numbers for the 2014-2015 academic year.)

College of Engineering Awards

Applying to the MEng program with EECS automatically makes you a candidate for the college's merit-based grant (also called Fung Fellows). There is also an Opportunity Grant awarded to applicants who enhance educational diversity and demonstrate financial need and who have completed the grant financial and essay portions of the application.

Other Financial Aid Options

There are also a variety of scholarships, grants, and fellowships that you can apply to through the following websites:

Fellowships available for MEng Applicants applying for Fall 2016 Admission:


National Defense Science and Engineering Graduate (NDSEG) Fellowships

American Society for Engineering Education
1818 N Street NW, Suite 600
Washington, DC 20036

Phone: (202) 331-3516
Fax: (202) 265-8504
E-mail:
Homepage: http://www.asee.org/ndseg
ASEE Science & Engineering Fellowships Blog: http://blogs.asee.org/fellowships/

Deadline: TBA


The Paul and Daisy Soros Fellowships for New Americans

400 West 59th Street, 4th Floor
New York, NY 10019

Phone: 212-547-6926
E-mail: pdsoros_fellows@sorosny.org
Homepage: http://www.pdsoros.org

Deadline: November 1, 2015


National Physical Science Consortium Fellowships

National Physical Science Consortium
USC - RAN
3716 S. Hope, Suite 348
Los Angeles, CA 90007-4344

Phone: (800) 854-NPSC or (213) 743-2409
E-mail:
Fax:
(213) 743-2407
Homepage: http://www.npsc.org

Deadline: November 30, 2015


Natural Sciences and Engineering Research Council (NSERC)

Postgraduate Scholarships (PGS D or M)

Scholarships and Fellowships Division
350 Albert St.
Ottawa ON
CANADA K1A 1H5

Phone: (613) 995-4273
E-mail:
Homepage: http://www.nserc-crsng.gc.ca/Students-Etudiants/PG-CS/BellandPostgrad-BelletSuperieures_eng.asp

Deadline: October 15, 2015

Frequently Asked Questions

I did not major in electrical engineering or computer science as an undergraduate student. Will I be eligible for admission into your program?

We have numerous applicants who are "career changers" and our best advice for you is to show within your application that you have the prerequisite knowledge and skills to succeed in this challenging program. This can include coursework, projects, industry experience, publications, letters of recommendation, and more. Succeeding in courses at UC Berkeley Extension (or another institution) could be a useful addition to your application.


Is there a faculty member that I can contact to ask questions about the program?

Our department receives thousands of admissions applications per year, so our faculty members are unable to respond to admissions inquiries. Our Masters Student Services Advisor (see Contacts) will be happy to field any of your admissions questions.


My TOEFL or GRE official scores have not yet been received according to my application; what should I do?

As long as you have entered your self-reported scores into the application, then we can use those for the review process, and once decisions are sent out, we will contact those admitted applicants whose official scores we still need.


What kind of financial assistance is offered for this program?

The College of Engineering offers two kinds of grants to ~30% of the M.Eng. student population: merit-based and need-based grants. Most students will be responsible for the entire cost of attendance for the program, and should plan carefully to ensure adequate financial resources.

Consideration for our merit-based grants (also called Fung Fellows Award) and need-based grants (also called Opportunity Grants) are based upon the information provided on the admissions application.

All applications are automatically considered for the merit grants, and a portion of top candidates are awarded grants that cover about 1/3 of the tuition. Applicants that have completed the financial portions of the application will be considered for the Opportunity Grant.


Please visit the Fung Institute FAQ for additional information.

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