A three-week intensive summer school teaching Computer Vision Methods for Ecology, seeking to empower ecologists to accurately and efficiently analyze large image, audio, or video datasets using computer vision.

Hosted at Caltech and supported by the Resnick Sustainability Institute in partnership with the Caltech AI4Science Initiative, and co-sponsored by Microsoft AI for Earth and Amazon AWS.

Please answer questions below and then upload application materials to:  
                   
                 https://caltech.app.box.com/f/b69c8ead6da44a38b920103352156364


Please label each file as indicated.

1. LastName_FirstInitial_Proposal (11pt Times Roman, 1" margins)

   1-page project proposal (11pt font, 1" margins) addressing the following:

    - Research problem -- What question are you interested in and how would computer vision methods better enable you to address it?
    - Data -- What type of data do you plan to work with? Do you have the data already in hand? How much data do you have, how much will you have by the time the summer school will start? Is the data labeled already, or do you need to develop a labeling plan?
    - Impact/Outlook -- What is the likely impact of your research for science, policy, education and conservation?

2. LastName_FirstInitial_Statement

    1-page personal statement (11pt font, 1" margins) describing your accomplishments, skills and career objectives.

3. LastName_FirstInitial_CV
    - CV (2 page max)
4. (Optional) LastName_FirstInitial_Video
    - 5’ video with a presentation of your work and the proposed project

Please ask your reference to upload their letter to the same box link, and title the letter LastName_FirstInitial_LetterofRef