KDD Startup Travel Awards 2017, USA


Deadline:

June 16, 2017


Opportunity Cover Image - KDD Startup Travel Awards 2017, USA

KDD 2017 Startup Travel Awards Call for Applications

KDD 2017 has obtained financial assistance from ACM SIGKDD to sponsor a limited number of Startup Travel Awards. These Awards will facilitate the participation of employees of startups, working in the broadly understood Data Science area, in KDD 2017. Priority will be given to attendees who have an accepted paper either in the main KDD 2017 conference program (either Research Track or Applied Data Science Track), or in one of the Workshops.

KDD 2017 invites applications for Travel Startup Awards. Interested, eligible individuals should apply by June 16, 2017, sending the following information to treasurer2017@kdd.org:

  1. Applicant’s Name, affiliated company, position in the company, applicant’s location
  2. Level of the Award applied for, and the approximate budget sought (in US$)
  3. A letter, on the company letterhead, signed by the company’s CEO, giving basic information about the company (date of incorporation, number of employees, total funding - in US$ - secured from start to now.) Only companies with total funding not exceeding US$5M are eligible.
  4. A link to the company’s website.

Awards will be granted on a competitive basis. Two levels of Awards will be considered, and the level of the awarded funding will be decided by the Startup Travel Awards Committee:

  • Amount of registration fee (early bird level)
  • Amount of registration fee + up to US2000 for travel and lodging.

The Startup Travel Awards Committee will inform the applicants by email about its decisions by June 23, 2017. Successful applicants will be expected to front the cost (both registration and travel), and will be subsequently reimbursed the cost up to the amount of the Award they have received.

For more information please click "Further Official Information" below.



Eligible Countries
Host Country
Opportunities
Publish Date
June 07, 2017
Link To Original




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