About the Program
A research-driven, faculty-mentored internship offering hands-on exposure to advanced research areas including Artificial Intelligence, multimodal systems, materials science, semiconductor physics, marketing, consumer behavior and sports management. Interns will work on defined research themes; they will learn and contribute to ongoing projects, and develop analytical, technical, and research skills in a structured academic environment.
Program Information
Duration
Internship duration
Application Deadline
Last date to apply
Internship Start Date
Program commencement
Internship End Date
Program completion
Eligibility Criteria
- UG: 3rd / 4th year (B.Tech / B.E / B.Sc / BBA or equivalent)
- PG: 2nd year (M.Tech / M.Sc / MBA or equivalent)
- Strong academic background preferred
- Relevant knowledge depending on domain (AI/ML, Physics, Materials, Sports Management etc.)
Application & Selection Process
Application Process
The application for the Jio Institute Summer Research Internship Programme 2026 is conducted entirely via email to ensure a personalized review of every candidate’s research potential.
Step 1: Prepare Your Application Documents
- Comprehensive CV: Highlight your academic performance (CGPA), relevant projects, technical and any prior research or industry experience.
- Research Synopsis: A brief statement (minimum 500 – maximum 1000 words) outlining your interest in a specific research theme offered by our faculty. Mention why you chose the topic and how your background prepares you for it.
Step 2: Subject Line Formatting
Format: Application for Summer Research Internship 2026 – [Your Name] – [Faculty Name/Research Area]
Example: Application for Summer Research Internship 2026 – Rahul Sharma – Dr. Sudipta Roy (AI for Healthcare)
Step 3: Submit via Email
Send the following documents by email on : summer.school@jioinstitute.edu.in
- CV
- Synopsis
- Following Academic Document:
- For Undergraduate (UG) applicants: Marksheets for Class 10, Class 12, and all available semester results.
- For Postgraduate (PG) applicants: Marksheets for Class 10, Class 12, Undergraduate degree/marksheets, and all available postgraduate semester results.
Important Instructions for Applicants
- Please apply to only one research area that best aligns with your skills and career goals.
- All interns are required to possess a personal laptop for work-related tasks during the 8-week period.
- This is a full-time, campus-based residency program. Candidates must be available from 1st June 2026 to 31st July 2026.
- Applications are reviewed as they arrive. Since there are only 10 to 12 seats available across all faculty projects, early submission is highly recommended.
Selection Process
The selection for the Summer Research Internship is a rigorous and competitive process designed to identify candidates with strong academic foundations and a genuine passion for research.
1. Preliminary Screening & Review
Applications are meticulously reviewed by our core academic committee as they arrive, early submission is highly recommended:
- Consistency in academic performance (CGPA/Percentage).
- The relevance of the applicant’s background to the chosen research theme.
- The quality and clarity of the submitted synopsis, showcasing the applicant's understanding of the research topic.
2. Faculty Interaction (Virtual)
Shortlisted candidates will be invited for a virtual interaction with the respective Faculty Mentors. This stage is crucial for:
- Discussing the applicant’s technical proficiency in mandatory tools.
- Assessing the candidate's analytical mindset and willingness to tackle complex, open-ended research problems.
- Ensuring alignment between the intern’s learning goals and the project’s objectives.
3. Final Selection & Communication
Following the interactions, the final selection is made based on a holistic evaluation of the candidate’s profile and interview performance. Successful candidates will receive a formal offer letter via email.
Stipend
Rs. 10,000/- per month for Undergraduate students and Rs. 20,000/- per month for Postgraduate students
Accommodation will be provided on campus on a double occupancy basis and is mandatory as interns will be working closely with the faculty.
Food is not included in the accommodation.
Faculty Supervisors & Research Areas
Dr. Sudipta Roy
Advanced AI for Healthcare & Scientific Systems
Requirements:
- Prior experience in Deep Learning, Computer Vision or work involving LLMs/VLMs is desired.
- Familiarity with DL frameworks such as PyTorch or TensorFlow is mandatory.
- Ability to write clean, modular, and scalable code.
- Prior experience in Python is mandatory.
Dr. Samik Mukherjee
Materials Science for Optoelectronics & Energy Devices
Requirements:
- Basic programming skills in Python or MATLAB for data analysis and simple modeling are desirable but not mandatory.
- Interest in semiconductor materials, nanoelectronics, optoelectronic devices, or advanced materials characterization.
- Familiarity with basic laboratory techniques, experimental data analysis, or numerical modeling will be an advantage.
- Ability to work independently, analyze experimental or simulation results, and communicate findings clearly in written and oral form.
Dr. Mohna Chakraborty
Next-Gen AI Systems (LLMs, Multimodal & Ethical AI)
Requirements:
- A strong foundation in Mathematics/Statistics/Computer Science.
- High proficiency in programming, particularly in Python.
- Prior experience in Natural Language Processing (NLP), Deep Learning, or work involving LLMs/VLMs is mandatory.
- Familiarity with DL frameworks such as PyTorch or TensorFlow is mandatory.
- Ability to write clean, modular, and scalable code.
Dr. Vishnu Prasad
AI in Consumer Behavior, Marketing & Digital Ecosystems
Requirements:
- Academics: Strong record (preferably top 20% or CGPA ≥ 7.5/10 or equivalent).
- Skills: Python is needed but students open to learn are also invited.
- Plus: Exposure to consumer behavior/marketing, AI/digital tech, or ML basics (not mandatory).
- Commitment: Full-time during the internship; strong motivation for interdisciplinary research.
Dr. Anuj Vora
Machine Learning, Decision Systems & Game Theory
Requirements:
- Basic knowledge of mathematical optimization, probability, calculus, machine learning algorithms
- Experience in multi-armed bandits, information theory, game theory, graph theory is a plus
- Working knowledge of any programming language
- Analytical mindset with a desire and willingness to learn
Prof. Anirudh Kalia
Talent & Competitions Pathways for school athletes
Requirements:
- Must have represented at District or State level in any sport
- Strong working proficiency in Microsoft Excel
- Must possess a personal laptop
Contact Details
If you need any further details or assistance regarding the programme, please feel free to reach out to us. We’ll be happy to help you.