NIT Meghalaya is organizing Matrix Classes in Solving the Linear Complementarity Problem, Apply by 31st October 2022

Overview :

NIT Meghalaya is inviting applications for  Matrix Classes in Solving the Linear Complementarity Problem, interested candidates can apply.

 

 

 

Who can attend?

  • Students at all levels (BTech/MSc/MTech/PhD).
  • Engineers, researchers, and faculty from academic and technical institutions

 

 

 

Module :

15 hours of Lectures and 4 hours of Tutorials: December 12 to December 16, 2022 Number of participants limited to fifty

 

 

 

Course Fees :

  • The participation fees for taking the course are as follows:
  • Participants from abroad: US $200
  • Industry/ Research Organizations: INR 10000
  • Academic Institutions: INR 5000 (Faculty/Postdoc), INR 3000 (Ph.D/MTech students) INR 1500 (M.Sc/BTech).

The above fee includes all instructional materials, tutorials, assignments, laboratory usage, working lunch, and refreshments on course session days. Limited participants will be provided with accommodation on a payment basis (subject to availability in the hostels) with an early reservation.

 

 

 

 

Mode of Registration :

  • Step-1: One-time Web (Portal) Registration: All prospective participants need to do web registration on the GIAN (https://gian.iitkgp.ac.in/GREGN/index) portal by making a one-time non-refundable payment of Rs. 500/, in case not registered before.
  • Step-2: Course Registration (Through GIAN Portal)
  • Step-3: After GIAN Registration the Course fee is to be deposited online in the institute account. The program fee covers the course materials and access to all the sessions. Participants should pay the course fee through online mode (NEFT/IMPS) and fill up transaction ID/details in the google form with the link and the account details given below.
  • Step-4: After online payment of the course fee, fill out the google form Registration link given below: https://forms.gle/AUfWTsemkKEVnP9s5
  • The last date for registration is 31st October 2022.

 

 

 

 

How to apply Apply Here




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