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Principal Project Associate-I

Organization: ICAR-Indian Agricultural Research Institute
Apply By: 06 May 2025
Location:
About the Organization
The journey of Indian Agricultural Research Institute (IARI), popularly known as Pusa Institute, began in 1905 at Pusa (Bihar) with the generous grant of 30,000 pounds from an American philanthropist, Mr. Henry Phipps. The institute was then known as Agricultural Research Institute (ARI) which functioned with five departments, namely Agriculture, Cattle Breeding, Chemistry, Economic Botany and Mycology. Bacteriology unit was added in 1907. The name of ARI was changed to Imperial Institute of Agricultural Research in 1911 and, in 1919 it was renamed as Imperial Agricultural Research Institute. Following a devastating earth quake on 15th January 1934, the institute was shifted to Delhi on 29th July 1936. Post independence, the institute has been renamed as Indian Agricultural Research Institute (IARI)
Education Qualification/Required Skills & Experience
Essential:
- MSc/MTech/ME/MCA in computer science/ Information Technology/Geomatics/Geo-informatics/Data Science/Data or System analytics/AI/ML/or equivalent from a recognized university/institution with first class or >7.5% OGPA
- 2 years working experience in R&D/ Academic/ Science and Technology Organizations
- Candidates should have done 4/5 years bachelor’s degree.
- Those with 3 years bachelor’s degree must have UGC/CSIR/ICAR NET/ MHRD-GATE qualification or Ph.D in any of above disciplines. (As per ICAR memorandum F.No. Agri. Edn./6/27/2014/HRD Dated 13.07.2015 and F.No. Agri. Edn./6/27/2014/HRD Dated 09.10.2015)
OR
- PhD degree in above subjects from a recognized university
- 4-year experience in R&D/ Academic/ Science and Technology Organizations
Desirable:
- Proficiency in satellite data analysis, GIS tools, ArcGIS, Web GIS, GEE, and programming proficiency in C#, Java, Python, R, ASP, IDL programming languages, 3D graphics/animation/3-D modeling, and handling databases knowledge crop simulation models, and analysis of climate model data
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