Applications are invited for Project Post-Doctoral Fellow at IIT Kanpur for the year 2025. The last date of application is April 30.
About IIT Kanpur
Indian Institute of Technology, Kanpur, established in 1959, is one of the premier institutions established by the Government of India. The aim of the Institute is to provide meaningful education, to conduct original research of the highest standard and to provide leadership in technological innovation.
Eligibility
- Ph.D. in computer science/engineering, electrical engineering, or related fields.
- Strong technical background in setting IoT hardware, sensors, networks, and machine learning.
- Sound publication record in high-impact conferences/journals.
- Experience in working as a member of a team in a collaborative environment.
- Strong mathematical and analytical skills.
- Experience with programming languages, especially Python and C/C++.
- Excellent written and verbal communication skills in English.
Nature of position
Temporary/Contractual
Location
IIT Kanpur
Duration of appointment
1 Year or till the end of the project (whichever is earlier), renewed annually based on performance
Nature of Work
This research has been funded by Jal Jeevan Mission, Indian Ministry. The successful postdoc should be able to decide the sensors and IoT devices, deploy them on the small testbed in the campus for water management. This research requires extensive experiments to collect sensor data, and advanced analytical techniques (statistics and machine learning) to understand water flows, leakages and water quality.
How to Apply?
Interested candidates may apply via email (to deepus283@gmail.com ) ONLY giving full details of qualifications and experience in Resume with copies of relevant certificates by April 30, 2025.
Salary
INR 60000-5000-85000 per month consolidated (Salary shall be commensurate with experience & skills)
Selection
The department reserves the right to fix suitable criteria for short listing of eligible candidates satisfying qualifications and experience. The selection will be based on offline and/or online interview. Only shortlisted candidates will be informed via email about the date of interview.
