Impart rigorous training in modern physics principles for students to formulate a physics problem based on a real-life situation. Provide analytical and computational training to solve mathematical problems in physical and engineering contexts. Provide laboratory training to test theory concepts, realise measurement limitations and errors, and design basic experiments based on simple building blocks. Impart conceptual and skills training in engineering foundations vital for any design work. Students can take electives in advanced physics topics or different areas of engineering based on their interest. Expose students to instrumentation used for frontier research in physics and engineering. Engage students with the research literature to help them write and speak confidently about recent developments in physics and engineering.
Building on this foundation, BS in Engineering Physics and MS in Quantitative Finance combines the mathematical methods of physics with core quantitative finance, covering asset pricing theory, stochastic calculus, derivatives, term-structure modelling, and portfolio management. It extends modelling into financial applications by integrating machine learning, artificial intelligence, large language models, big data analytics, and algorithmic portfolio optimisation. Practical training is emphasised through hands-on computational tools—including Bloomberg Analytics, Python, R, MATLAB, SQL, and Stata—complemented by practical skill workshops, an industry summer internship, and an applied Master’s capstone project.
Learning Outcomes
The BS in Engineering Physics and MS in Quantitative Finance programme empowers students to tackle complex, interdisciplinary challenges and innovate at the forefront of technology. Students who graduate with this major can pursue higher studies in physics and engineering or seek professional opportunities in diverse areas of modern technology like advanced materials and nanotechnology, renewable energy, microelectronics and photonics, data science, computational physics, quantitative research and modelling, algorithmic trading, financial engineering, risk analytics, and quantitative portfolio management. Graduates are equipped to apply probability, statistics, stochastic calculus, and optimisation to model and solve financial engineering problems such as pricing, hedging, and portfolio construction. They can critically evaluate financial models, their underlying assumptions, and regulatory environments, while performing econometric forecasting and risk analysis using Value at Risk (VaR), Expected Shortfall, stress testing, and scenario analysis. Additionally, students learn to implement computational solutions in programming languages and communicate quantitative analysis clearly while incorporating professional ethics and risk management safeguards into practice.
Programme Details
Exit Option: If a student enrolled in the BxMx Programme chooses to exit from the programme, then they have the option of getting a Bachelor’s (Honours) degree by meeting the requirements of any of the majors.
| Offered by | School of Arts and Sciences and Amrut Mody School of Management |
| Programme | |
| Degree | Bachelor of Science in Engineering Physics and Master of Science in Quantitative Finance |
| Minimum Programme Credits | 200 |
| Minimum Major Credits | |
| Credits | |
|---|---|
| Foundation Programme (Three Studios) | 9 |
| First Year Seminar on Critical Thinking and Writing | 3 |
Note: If a student’s performance in the First Year Interdisciplinary Seminar Course is unsatisfactory, they will have to retake the course during a specified time window.
| Credits | |
|---|---|
| Humanities and Languages | 3 |
| Social Sciences | 3 |
| Biological and Life Sciences | 3 |
| Mathematical and Physical Sciences CSD105 Data Science |
3 |
| Performing and Visual Arts | 3 |
| MAT396 Numerical Methods | 3 |
| GER Elective 1 | 3 |
| GER Elective 2 | 3 |
| COM101 Effective Reading and Comprehension Skills | 3 |
| Sports and Wellness | 3 |
Notes:
|
Major Requirements |
Credits |
|---|---|
| Major Core | 77 |
| Core Mathematics Courses | 10 |
| MAT281 Multivariable Calculus | 4 |
| MAT256 Differential Equations | 3 |
| MAT248 Applied Linear Algebra | 3 |
| Core Physics Laboratory Courses | 12 |
| PHY121 Laboratory Physics- Mechanics | 3 |
| PHY122 Laboratory Physics- Electromagnetism | 3 |
| PHY221 Laboratory Physics- Optics | 3 |
| PHY3XY Laboratory Physics- General Properties of Matter | 3 |
| Engineering Foundation Knowledge Core Courses | 21 |
| ENR106 Introduction to Programming | 3 |
| ENR108 Materials and the Engineering World | 3 |
| ENR209 Mechanics of Rigid Bodies | 2 |
| ENR210 Continuum Mechanics | 2 |
| PHY313 Thermodynamics | 4 |
| PHY314 Electrical Circuits and Electronics | 4 |
| PHY321 Laboratory Physics - Electronics | 3 |
| Engineering Foundation Skills Core | 9 |
| ENR114 Engineering Visualisation and Drawings | 2 |
| ENR105 Product Dissection and Realisation | 2 |
| ENR215 Design, Innovation and Making | 2 |
| ENR206 Sensors, Instruments and Experimentation | 2 |
| ENR307 Communication III: Technical Communication | 1 |
| Core Physics Theory Courses | 25 |
| PHY111 Introductory Mechanics and Relativity | 4 |
| PHY112 Electromagnetic Theory | 4 |
| PHY212 Oscillations, Waves and Optics | 3 |
| PHY310 Quantum Mechanics | 4 |
| PHY316 Solid State Physics | 3 |
| PHY318 Atomic and Molecular Physics | 3 |
| PHY319 Statistical Mechanics | 4 |
| Major Electives | 9 |
Notes
University recognises the evolving expectations of employers, who seek adaptable, tech-savvy, and well-rounded individuals with strong communication, problem-solving, and teamwork abilities. Accordingly, the university integrates structured skill courses delivered through both internal and external platforms to prepare students as “T-shaped” professionals capable of applying knowledge effectively in diverse professional contexts. Skill courses are designed and offered with an aim to develop applied, demonstrable capabilities aligned with career aspirations and job roles.
Note: Courses can be taken from an existing list or approved On-campus courses and MOOCs for additional credits over and above what is required for the The BxMx Programme. See document Mapping Skills to Jobs.
Free electives let students pursue any particular area in more depth, develop alternate areas of expertise, or learn more about many other interests. They provide flexibility for customising education at the University. It can take the following form:
Note: Courses can be taken from an existing list or approved On-campus courses and MOOCs for additional credits over and above what is required for the The BxMx Programme
A summer internship offers invaluable professional experience and the chance to develop specific, employable skills. It provides an excellent opportunity to explore potential career paths post graduation or discover new graduate programme interests. This experience connects with industry, often serving as a direct stepping stone to a job offer. Most of our programmes include a mandatory internship requirement.
It's advised that you start thinking about internships early in the monsoon semester. You may seek advice from the Career Development Centre.
Note: Any internship requirement for the undergraduate programme is subsumed in the 3 credit Summer Internship in the master’s programme.
All students will complete 45 hours of community engagement to develop a sense of social responsibility, enhance problem-solving skills, and understand their role as engaged members of society. They must undergo a mandatory course, VOL101 Engagement with Society, which is a graduation requirement. Students are advised to complete the course during the first two years at the University. Volunteer work could include teaching underprivileged children, participating in adult literacy programmes, distributing blankets or other items, working with old age homes and orphanages, providing support and encouragement to patients at hospitals, cleaning heritage sites, engaging with workers on campus, operating a food bank, engaging with the police, municipal government, zoo, sanitation services, etc.
|
Programme Requirements |
Credits |
|---|---|
| Programme Core | 48 |
| Programme Electives | 9 |
| Immersive Skill Workshop (Illustrative) | 3 |
| Financial Analytics using Bloomberg | |
| Financial Analytics using R/Matlab/SQL | |
| Project involving Bloomberg Analytics | |
| Generative AI for Financial Analysis and Reporting | |
| Blockchain and DeFi Protocol Modeling | |
| Algorithmic Portfolio Optimisation with Python | |
| Technical Chart Analysis: Seminar/Masterclass | |
| Generative AI and Large Language Models (LLMs) for Alpha Generation | |
| Master's Capstone Project | 6 |
Note: The course FAC133 Financial Management is an antirequisite of the course FAC533 Corporate Investments and Value Creation. Thus, a student who is interested in pursuing MSQF may not take FAC133.