Ram Lal Anand College โ University of Delhi
| Last Date to Apply | 07 Aug 2026 |
|---|---|
| Interview Date | 08 Aug 2026 |
| Post Name | Field Investigator |
|---|---|
| Total Vacancies | 1 |
| Qualification | M.Tech or M.Sc in Computer Science/Cyber Security/IT/Digital Forensics |
| Age Limit | Refer to official notification |
| Salary | INR 40,000/- p.m. |
| Application Fee | Not mentioned |
| Selection Process | Online Interview |
Ram Lal Anand College, University of Delhi, has initiated the recruitment process for one Field Investigator position under project-based requirements. This contractual role offers a consolidated monthly remuneration of INR 40,000. Interested candidates meeting the academic prerequisites should submit their applications via the designated online portal by the prescribed deadline.
| Post Name | Vacancies | Salary |
|---|---|---|
| Field Investigator | 1 | INR 40,000/- p.m. |
Candidates must possess the following educational qualifications to be eligible for the position:
| Event | Date |
|---|---|
| Application Deadline | 2026-08-07 |
| Interview Date | 2026-08-08 |
Securing a government position under Ram Lal Anand College requires a disciplined and strategic approach. Candidates with M.Tech or M.Sc in Computer Science/Cyber Security/IT/Digital Forensics qualifications should focus on the following:
To avoid fraud and secure your candidature for the Field Investigator position, always complete the following checks before submitting your application:
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The educational qualification required for this recruitment is: M.Tech or M.Sc in Computer Science/Cyber Security/IT/Digital Forensics. 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.