Title: "Waterlix Remote Sensing and AI Solutions for Water Management"

Project Description: Waterlix is a company that uses artificial intelligence to solve water-related problems, providing insights for managers and experts in municipalities, water utilities, or watershed management organizations.

The goal of this internship is for students to reach out to conservation areas and farming complexes to gather information on their water management needs and interests. This may include monitoring changes in their area, such as the health of trees or pollution in rivers and lakes, or determining the best distribution of water in farmland to maximize crop yields. The students will work with the conservation areas and farming complexes to understand their specific needs and requirements for remote sensing reports. Additionally, the students will also gather information about the responsibilities and main duties of the conservation areas and farming complexes, as well as any new challenges they face from an environmental perspective or changes in regulations that may affect their processes.

Duties:

  • Collaborate with the supervisor to work on the above project

  • Contact conservation areas and farming complexes to gather information on their water management needs and interests

  • Understand the specific needs and requirements for remote sensing reports

  • Gather information about the responsibilities and main duties of the conservation areas and farming complexes, as well as any new challenges they face

Requirements:

  • Enrolled in one of the following programs or related ones: Environmental Sciences, Hydrology

  • Interested in research and be open to exploring new fields if needed to solve the problem

Placement Location: Remote

Start Date: ASAP

End Date: Open

Day of the week / # of hours: flexible

This internship will allow students to gain hands-on experience in remote sensing applications and requirement gathering, as well as an understanding of the water management needs and interests of conservation areas and farming complexes. This will help students to understand how their environmental background can be used to solve real-world problems and how they can be applied to remote sensing.