UCLA MQE Labs: Applied Research Projects Driving Innovation and Career Success

The UCLA Master of Quantitative Economics (MQE) program distinguishes itself through its emphasis on hands-on learning and real-world application of data analytics, economics, and finance. A cornerstone of this approach is the MQE labs research projects, which provide students with invaluable opportunities to collaborate with corporate partners, tackle complex business challenges, and develop sought-after skills.

Applied Projects: Bridging Theory and Practice

Applied projects serve as a critical bridge between the theoretical knowledge gained in the classroom and the practical demands of the professional world. As an MQE student, you’ll have the opportunity to apply your data analytics and economic research skills to help corporate partners solve business challenges. These projects allow students to put their classroom knowledge to work on real business challenges. By working in small teams under the guidance of a faculty coach, students analyze data, develop insightful solutions, and present their recommendations to company executives. These experiences significantly enrich resumes and provide hands-on experience in data analysis and finance.

One example of an applied project in action involves MQE students teaming up with Sustento Group to tackle a real-world challenge in clean energy. For this applied project, one team analyzed energy-use data from buildings throughout Los Angeles to present recommendations for sustainable retrofits. The company sponsor, Sustento Group, extended a job offer to a student at the end of the project, who joined them following graduation.

Other examples of applied projects include:

Constructing an ensemble model of Machine Learning to make a portfolio by analyzing data on a buyside investment platform.
Developing an empirical strategy to calculate the payoff of a new customer for a cybersecurity firm and presenting business recommendations to increase the future win rate of sales.
Performing predictive analysis on 40,000+ buildings in Los Angeles to identify total cost savings and investment costs provided buildings comply under specific HVAC requirements.
Analyzing a complex dataset to recommend strategies to increase ad revenue.
Combining text engineering and machine learning to conduct portfolios that give a higher rate of return than the S&P, using Rolling Window for Training and Testing split to ensure that the algorithms will work well in the real-world.

The applied project experience enhances the overall MQE learning experience and can lead to internship opportunities.

Benefits for Students and Corporate Partners

The MQE labs research projects offer mutual benefits for both students and corporate partners.

For Students:

Hands-on Experience: Applied projects provide invaluable hands-on experience in data analysis, modeling, and problem-solving.
Resume Enhancement: Participation in these projects significantly enriches students' resumes, making them more competitive in the job market.
Networking Opportunities: Students gain exposure to company executives and industry professionals, expanding their professional networks.
Career Advancement: Applied projects can lead to internships and full-time job offers from sponsoring companies.
Skill Development: Through these projects, students develop critical skills in teamwork, communication, and presentation.
Practical Application of Knowledge: Applied projects offer the chance to put classroom knowledge to work on real business challenges.

For Corporate Partners:

Access to Top Talent: Companies gain access to the skills and expertise of talented MQE students.
Innovative Solutions: Students bring fresh perspectives and innovative solutions to complex business problems.
Cost-Effective Research: Applied projects offer a cost-effective way for companies to conduct research and development.
Recruitment Opportunities: Companies can identify and recruit top MQE graduates for internships and full-time positions.
Collaboration with Faculty: Corporate partners benefit from the guidance and expertise of UCLA faculty.
Addressing Unique Needs: Partner with UCLA’s Master of Quantitative Economics (MQE) students on short-term applied research or business projects that address your organization’s unique needs. Open to organizations of all sizes and sectors.

Many corporate partners have hired MQE students following their applied projects-either to implement the recommendations developed during the project or to continue and expand on the work beyond the project timeline. These outcomes reflect the quality of our students’ work and the real-world value they bring to organizations.

Career Development and Industry Connections

The MQE program is committed to providing students with a supportive career community and employer connections. The MQE actively partners with global companies in finance, consulting, analytics, data science, tech, business, and marketing, among other fields.

The MQE program hosts a variety of events to bring hiring organizations and student talent together. Throughout the year the program will host networking events, career panels, training workshops and career fairs to connect you with global employers. Career coaches are available to discuss your career goals and provide resources and advice to help you reach your career goals. A writing coach is available to help you with resume and cover letters.

Many MQE students complete professional internships during the program. Some students choose to extend the program over 4-6 quarters, to allow for a summer internship between their first and second year of the program.

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The demand for talent with extensive quantitative, analytical, and financial training has never been stronger. Given the hands-on nature of our curriculum, graduates are well qualified for positions which require advanced economics, data analytics, finance training or extensive quantitative background. Many of our graduates have gone on to coveted positions with Central Banks, International Organizations, Government Ministries, consulting firms, think tanks, Fortune 500 companies, and banks. The MQE has robust industry connections to help students secure competitive internships and full-time opportunities around the globe. Each year, a few students will choose to pursue a PhD following their MQE degree.

Curriculum and Skills Development

The MQE program is focused on training students in data analytics, econometrics, machine learning, applied statistics, quantitative methods, forecasting, data mining and finance through hands-on courses, applied business projects, research activities, group work, and assignments. Students will gain exposure to R, Python, SQL, Excel and numerous financial platforms and tools throughout the program. The unique hands-on curriculum and approach equips graduates with the applied concepts, technical tools, and analytical skills necessary to solve complex business problems facing government agencies, financial institutions, and global corporations.

The MQE is a 48-unit degree program. Students can complete the degree in as few as 9 months (or 3 quarters - Fall, Winter and Spring). However, students may choose to extend the time of the program up to 18 months (4, 5, or 6 quarters). All students are required to take a foundational course in applied statistics and econometrics (Econ 430 and 441A) during their first term and enroll in Economists in Action (Econ 410) each term.

The program also emphasizes the development of professional skills essential for success in professional business settings. It aids students in translating topics covered in other courses into language and format that is accessible to industry/non-academic settings. Students conduct labor market research, identify and analyze industry trends, and develop targeted plan to achieve professional success.

Some of the key courses and skills covered in the MQE program include:

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Applied Statistics and Econometrics: Introduction to probability, statistics, econometrics, and time series methods using R and Python.
Asset Valuation: Introduction to core principles of asset valuations with emphasis on common economic reasoning used in valuation problems.
Financial Accounting: Understanding financial reports designed to reflect corporate performance and financial condition.
Data Management: Introduction to modern practices in data gathering, cleaning, and warehousing, including Web scraping using APIs, engineering of R packages, and data manipulation in SQL. Students gain hands-on experience with SQL database queries and database management through integrations with database management systems, query editors, and Python and R programming languages.
Fundamental Analysis: Measuring a security’s value by assessing economic and financial factors.
Social-Emotional Learning: Developing social-emotional learning skills through interactive activities and lessons to improve abilities to succeed in variety of team settings, stress reduction, emotion management, and team building.
Machine Learning: Covers set of fundamental machine learning algorithms, models, and theories, and introduces advanced engineering practices for implementing data-intensive intelligent systems.
Financial Data Science: Modeling financial data and testing hypotheses on how markets work and prices are formed.
Data Visualization: Developing data visualization skills using Tableau and Python packages.
Cloud Services for Big Data: Introduction to cloud services software relevant for big data analytics and data scientists, including Amazon Web Services.
Economic Forecasting: Introduction to theory and application of cutting-edge tools used by economists and business leaders to inform their views of economy.
Modern Data Management Systems: Exposes the students to cutting-edge data management concepts and systems and provides the students the working knowledge needed to manage large-scale data.
Business Intelligence Software: Introduction to Business Intelligence software relevant for Big Data and Financial Services companies, including Amazon AWS, PowerBI, and Hadoop.

MQE students may also take select PhD courses within The Department of Economics.

Labs and Research Centers at UCLA

Beyond the MQE program, UCLA boasts a wide array of research labs and centers that contribute to cutting-edge advancements across various fields. While not directly part of the MQE program, these labs showcase the breadth and depth of research opportunities available at UCLA. Some notable labs include:

The Active Materials Laboratory: Contains equipment to evaluate the coupled response of materials such as piezoelectric, magnetostrictive, shape memory alloys, and fiber-optic sensors.
The Advanced Space Systems and Propulsion Laboratory: Developing new approaches for fast, low cost and easy to access exploration of space.
The Anatomical Engineering Group: Researches anatomics, the coengineering of body and machine in pursuit of synergistic bionic performance.
AVSIL: A testbed for design, building, evaluation, and testing of hardware instrumentation and coordination algorithms for multiple vehicle autonomous systems.
The Biomechatronics Laboratory: Dedicated to improving quality of life by enhancing the functionality of artificial hands and their control in human-machine systems.
The Bionics Laboratory: Performs research at the interface between robotics, biological systems, and medicine.
The Boiling Heat Transfer Laboratory: Performs experimental and computational studies of phase-change phenomena.
TANMS: A multi-institutional engineering research center focused on research, technology translation, and education associated with magnetism on the small scale.
Chen’s Intelligence Laboratory: Focuses on artificial intelligent systems that simulate the learning functions of the human brain.
CCAS: A multi- and trans-disciplinary research center focused on fundamental and applied basic studies relevant to aerospace systems.
The Complex Fluids and Interfacial Physics Laboratory: Multidisciplinary, with areas of research ranging from rheology of biofluids to energy storage.
The Computational Fluid Dynamics Laboratory: Studies a variety of fluid mechanics problems with research interests in the areas of computational fluid dynamics, flow control, data science, network theory, and unsteady aerodynamics.
CyCLab: Investigates the neuronal mechanisms for information processing and learning.
The Dynamic Nucleic Acid Systems Laboratory: Develops mathematical models and experimental platforms to build adaptive and dynamic biological devices using DNA, RNA, and proteins.
The Energy and Propulsion Research Laboratory: Applies modem diagnostic methods and computational tools to the development of advanced rocket and airbreathing propulsion as well as energy systems.
The Flexible Research Group: Dedicated to the design and fabrication of flexible structures, mechanisms, and materials that achieve extraordinary capabilities.
The Fusion Science and Technology Center: Includes experimental facilities for conducting research in fusion science and engineering, and multiple scientific disciplines in thermofluids, thermomechanics, heat/mass transfer, and materials interactions.
H-Lab: Focused on understanding and engineering fundamental transport phenomena and new materials for wide applications including energy conversion, storage, aerospace, electronics, thermal management, micro/nano sensors, and biomedical devices.
The Hypersonics and Computational Aerodynamics Group: Primarily focuses on fundamental physics-based research of hypersonic flows using advanced numerical tools; and application of discovered fundamental knowledge to real-world aerospace systems, such as development of hypersonic planes and space vehicles.
NRT-INFEWS: Integrated Urban Solutions for Food, Energy, and Water Management: Combines research, education, and communication training to educate future leaders towards delivering comprehensive solutions to food, energy, and water systems (FEWS) challenges in urban systems under the pressures of global climate change.
The Laser Spectroscopy and Gas Dynamics Laboratory: Conducts research driven by applications in propulsion and energy, with extensions to health and environment.
Lin Lab: Research looks at developing 3D biological tissues that mimic the geometric structure, mechanical properties, and functionality of human organs.
The Mechanics of Soft Materials Laboratory: Investigates the fundamental physics and mechanics of soft materials, such as their constitutive relation, nonlinear deformation, instability, and fracture.
The Mechatronics and Controls Laboratory: Conducts research in theory and innovation in dynamic systems, controls, mechatronics, and robotics.
The Micro and Nano Manufacturing Laboratory: Explores physical phenomena unique in submillimeter scale, and utilizes microelectromechanical systems (MEMS) technologies to advance important knowledge and create useful applications.
The Modeling of Complex Thermal Systems Laboratory: Addresses a variety of systems in which heat transfer plays an important role.
The Morrin-Gier-Martinelli Heat Transfer Memorial Laboratory: Engaged in a broad range of interdisciplinary research projects at the intersection of interfacial and transport phenomena, radiation transfer, material science, and biology for sustainable solar energy conversion; waste heat energy harvesting; electrical energy storage; and energy efficient buildings.
MTSL: Focused on heat and mass transfer phenomena at the nano- to macro-scales.
The Nanoscale Materials and Devices Laboratory: Explores new methods of controlling light, heat and electric current flow with nanostructured and architectured materials for sustainable energy and communications applications.
The Nanoscale Transport Research Group: Works on a broad range of problems, primarily involving transport processes by electrons, phonons, photons, and fluids.
The Optofluidics Systems Laboratory: Develops heterogeneously integrated functional devices and systems for biomedical applications.
RoMeLa: A facility for robotics research and education with an emphasis on studying humanoid robots and novel mobile robot locomotion strategies.
The Scifacturing Laboratory: Furnishes a creative, interdisciplinary platform for science-driven manufacturing (scifacturing) as the next level of manufacturing.
The Sensors and Instrumentation Laboratory: Focuses on the design, fabrication, modeling, and testing of microscale sensors, notably coriolis vibratory gyroscopes.
The SOFIA Laboratory: Explores a wide variety of phenomena that occur in fluid flows in nature and technology.
SMERC: Performs research; creates innovations; and demonstrates advanced Internet-of-things, sense-and-control technologies, and data-enabled machine learning to enable development of the next-generation electric utility grid-the smart grid.
The Structures-Computer Interaction Laboratory: Employs a data-driven approach to the modeling and design of programmable smart structures.

Admissions and Program Information

Applications for Fall 2026 are now open. Applications are reviewed on a rolling basis. The application deadline is March 15, 2026. The MQE program is STEM Certified (CIP Code 45.0603: Econometrics and Quantitative Economics).

To apply to the UCLA MQE program, international applicants should submit transcripts in both the original language AND the authorized, complete, and exact English translation certified by the issuing institution. Degree and diploma certificates (or other evidence of conferral of all degrees, diplomas, or professional titles) must accompany the transcripts, and must also be submitted in the original language AND in English.

If your first language is not English, you must certify proficiency in English when you apply to UCLA. The MQE requires you submit TOEFL or IELTS scores as part of the admissions process. Official test scores will be required if you are admitted. TOEFL scores must be at least 87 on the internet-based test. If you score less than 100 on the TOEFL iBT, or less than 7.5 on the IELTS, you are required, upon arrival at UCLA, to take the ESLPE.

There are several housing options available for UCLA MQE students. The assignment of university housing is lottery-based. You must first create your personal student account at my.ucla.edu. The Community Housing Office (CHO) provides rental resources to the entire UCLA community. UCLA’s Veteran’s Resource Center offers programs, resources, events, and a connected community for Veterans.

Career Outcomes

UCLA’s MQE graduates secure post-MQE plans and are employed across a range of fields within six months of completing the program. 95% of MQE graduates secure post-MQE plans within 6 months of graduation, securing corporate roles as well as acceptance into pre-doctoral and Ph.D. programs. MQE grads are employed in almost every field imaginable, with most students accepting roles in data analytics, finance, consulting and tech.

The MQE program provides a supportive career community and employer connections to help MQE students secure internships, applied projects and full-time positions with companies around the globe.

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