National Institute of Technology Agartala
| Last Date to Apply | 07 Aug 2026 |
|---|
| Post Name | Technical Assistant Trainee |
|---|---|
| Total Vacancies | 4 |
| Qualification | B.E./B.Tech in CSE/IT/Data Science/AI or MCA with minimum 60% marks or 6.5 CGPA |
| Age Limit | Maximum 24 years |
| Salary | Rs. 25,000 per month (Fixed) |
| Selection Process | Written Test and Personal Interview |
The National Institute of Technology (NIT) Agartala has announced the recruitment for 4 Technical Assistant Trainee positions on a contractual basis. Candidates holding a degree in Computer Science, Information Technology, Data Science, or related fields, who graduated in 2024, 2025, or 2026, are eligible to apply. The application window is open until 07 August 2026.
| Post Name | Total Posts |
|---|---|
| Technical Assistant Trainee | 4 |
Candidates must ensure they meet the following educational and age requirements:
The selection process for the Technical Assistant Trainee positions involves a written test followed by a personal interview.
| Event | Date |
|---|---|
| Last Date of Application | 2026-08-07 |
Securing a government position under National Institute of Technology Agartala requires a disciplined and strategic approach. Candidates with B.E./B.Tech in CSE/IT/Data Science/AI or MCA with minimum 60% marks or 6.5 CGPA qualifications should focus on the following:
To avoid fraud and secure your candidature for the Technical Assistant Trainee position, always complete the following checks before submitting your application:
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The educational qualification required for this recruitment is: B.E./B.Tech in CSE/IT/Data Science/AI or MCA with minimum 60% marks or 6.5 CGPA. Please always refer to the official notification PDF linked in the "Source/Official Links" section above for the most accurate and complete eligibility criteria, including age limits, experience requirements, and category-specific relaxations.
Sneha Patel is a certified career strategist specializing in government competitive examinations. With her background in Economics and Data Analysis, she provides data-driven insights on exam patterns, cut-off trends, and preparation strategies.