CSIR-UGC NET June 2024 Results and Cut-Off Marks Announced Download PDF

The much-anticipated results for the CSIR-UGC NET June 2024 exam have been released. Conducted on July 25th, 26th, and 27th, 2024, this examination is critical for candidates aiming to qualify for Junior Research Fellowship (JRF) and Assistant Professor positions in various scientific disciplines. The CSIR-UGC NET exam opens doors for thousands of aspirants, providing opportunities to pursue Ph.D. programs and teaching positions across India.

For those who appeared in the exam, the official results and cut-off marks are now available. You can view the official notification and detailed results by downloading the CSIR-UGC NET Result PDF.

Click Here to Download the Result of CSIR-UGC NET: Download PDF

Click Here to Download the Cut-off of CSIR-UGC NET :Download PDF

Category-Wise Cut-Off Marks for CSIR-UGC NET June 2024

CSIR has set the minimum cut-off percentages for various categories, required to qualify for JRF and Assistant Professor roles. Below is a detailed table with subject-wise cut-offs for each category:

Junior Research Fellowship (JRF)

Subject	UR (%)	EWS (%)	OBC (%)	SC (%)	ST (%)	PwD (%)
Chemical Science	55.50	47.50	47.75	36.00	30.75	25.00
Earth Science	56.95	51.22	49.15	41.65	37.49	25.35
Life Science	99.08	96.52	96.44	91.79	87.82	69.13
Mathematical Science	58.88	50.75	49.75	37.00	30.63	25.38
Physical Science	43.81	36.00	37.19	28.56	26.25	25.19

Assistant Professor

Subject	UR (%)	EWS (%)	OBC (%)	SC (%)	ST (%)	PwD (%)
Chemical Science	49.95	42.75	42.98	32.40	27.68	25.00
Earth Science	51.26	46.10	44.24	37.49	33.74	25.00
Life Science	98.34	94.46	93.71	87.84	83.74	69.13

Results Overview

The CSIR-UGC NET June 2024 results have provided a significant step forward for many aspiring researchers and educators:

A total of 1,963 candidates have successfully qualified for the Junior Research Fellowship (JRF) under the CSIR JRF scheme. These candidates are also eligible to apply for Assistant Professor positions.
Additionally, 1,875 candidates have qualified for Junior Research Fellowship under the UGC JRF scheme and are now eligible for Assistant Professor roles.

Candidates can check their roll numbers in the list of successful candidates on the official CSIR HRDG website. This list contains all the relevant details, including qualification status and subject-wise ranks.

Important Points to Note

The merit list has been prepared based on the cumulative marks obtained in all parts of the exam (A, B, and C). There are no separate cut-offs for individual sections.
To qualify, candidates from the General, EWS, and OBC categories must have secured a minimum of 33% marks, while SC, ST, and PwD candidates have a minimum qualifying mark of 25%.
In subjects such as Life Science, the results have been calculated based on percentile scores. The raw marks were normalized into NTA scores, and the results were declared based on these percentiles.

FAQs

Question What is the cut-off for JRF in Life Science for the General category?

Answer: The cut-off for JRF in Life Science for the General category is 99.08%.

Question Are there individual cut-offs for each section of the CSIR-UGC NET exam?

Answer: No, the merit list is created based on the cumulative scores of all parts (A, B, and C) combined. There are no separate cut-offs for each section.

Question What is the minimum qualifying benchmark for General, EWS, and OBC candidates?

Answer: The minimum qualifying benchmark for General, EWS, and OBC candidates is 33%.

Question How can I check if I have qualified for the CSIR-UGC NET June 2024 exam?

Answer: You can check your result by looking for your roll number in the list of qualified candidates published on the CSIR HRDG website.

Question What is the minimum qualifying percentage for SC, ST, and PwD candidates?

Answer: The minimum qualifying percentage for SC, ST, and PwD candidates is 25%.

Question How were the results for Life Science declared?

Answer: The results for Life Science were declared using NTA scores (percentiles), where raw marks were normalized into percentiles.