M.Tech e-Mobility

Programme Overview

The M.Tech e-Mobility programme at the Department of Electronics and Electrical Engineering at MIT-WPU is designed to prepare students for careers in e-Mobility research and development. The programme focuses on helping students understand and apply complex systems in this field and addresses the challenges of working in the eMobility sector. By providing specialised training in this area, students develop the skills and knowledge needed to succeed in this field. Graduates emerge equipped for careers in fields like EV and Automotive, Hybrid Vehicles, Rapid Transit Systems, Battery Industry, EV Telematics, Autonomous Cars, EV Charging Infrastructure Development, Entrepreneurship and Research opportunities in EV Machine and Drives, Embedded Systems and Control, Power Electronics, Battery Technologies and Management Systems, Charging Infrastructures, Green Energy, EV Telematics and VANETs, EV Life Cycle Assessment, AI and Data Science, IoT and allied areas.

2 Years

Last Date To Apply : 17 May 2024
Programme Name

M.Tech e-Mobility

Fee Per Year

Rs. 1,95,000

Highest CTC


Minimum 50% aggregate score in graduation (4 years) of relevant Engineering Branch from UGC approved University or equivalent (at least 45% marks, in case of Reserved Class category candidate belonging to Maharashtra State only)
GATE Qualified (Obtained a positive score in GATE 2022, 2023, 2024) /MIT-WPU CET 2024 /PERA 2024
Sponsored Candidate (Need 2 years of work experience after graduation, in field related to graduation)

Selection Process

The Selection process for this programme is based on the merit of MIT-WPU CET 2024 score / PERA 2024 Score or GATE Score (2022/2023/2024) & Personal Interaction conducted by MIT-WPU.
For admission under sponsored category, candidate should have minimum two years of fulltime work experience in a registered firm/ company/ industry/ educational and/or research institute / any Government Department or Government Autonomous Organization in the relevant field in which admission is sought.

Programme Highlights
  • A focused curriculum on EV design and relevant hardware/software technologies, ensuring students are equipped with the latest industry knowledge.
  • State-of-the-art infrastructure with access to cutting-edge facilities like the Electric Vehicles Siemens Lab, Rubiscape Center of Excellence for TinyML and Data Science, and DOBOT Robotic Arm, provide hands-on training and research opportunities.
  • Strong ties with leading industry and research organisations such as Siemens, Inteliment-Rubiscape, Jendamark, ICTP-Italy, Tata Power Skill Development Institute, Texas Instruments, IBM, and KPIT, enhance industry exposure and networking opportunities.
  • The flexible nature of the programme allows working professionals to conduct research in their current organisations, enabling career advancement while pursuing higher education.
  • Explore diverse career opportunities in the rapidly growing automotive sector, particularly in Electric Vehicles (EVs) for a strong foundation and a successful career.
  • Valuable industry exposure through visits, interactive sessions, and workshops conducted by industrial experts, fostering practical knowledge and insights.
  • Opportunities to work on interdisciplinary projects encourage students to apply their skills across various domains for a holistic learning experience.
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Programme Outcomes
  • Adeptly apply mathematics, science, and engineering principles to solve complex engineering problems effectively.
  • Analyse and formulate solutions for complex engineering issues, drawing on extensive research literature and validating conclusions using foundational principles.
  • Design and develop solutions for intricate engineering challenges, ensuring they meet specified requirements while considering public health, safety, and environmental factors.
  • Conduct thorough investigations using research-based knowledge and methods, including designing experiments and interpreting data, to address multifaceted engineering problems with no straightforward solutions.
  • Utilise advanced engineering and IT tools, prediction models, and modern techniques to carry out complex engineering tasks, recognizing their limitations and implications.
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