GEOSPATIAL AI GRADUATE FOR GLOBAL ENVIRONMENTAL PROJECT
Location: based in Hong Kong
Start date: As soon as possible
Contract: Full Time
Can we quantify nature and the pace at which we are destroying it? Data is abundant, but also scattered, jargon-filled and poorly disseminated. Consequently, the true magnitude of human encroachment on natural ecosystems still eludes the public.
By leveraging artificial intelligence and remote sensing technology, Earth.Org’s Natural Capital Ledger seeks to create an interactive geospatial database which, just like an accounting ledger, takes stock of the current natural capital and tacks its historic rate of depletion.
By mapping the depletion of key natural capital assets, we hope to combat apathy, educate and advocate for countries to weave the principles of natural capital accountancy into their economic development policies.
We believe in the power of technology to address global issues. The Natural Capital Ledger will monitor the Earth’s health through satellite image mapping and derive insights into humanity’s encroachment on natural ecosystems by analysing changes in the environment over time.
The Main objective is to create the Natural Capital Ledger. This is a geo-spatial platform that combines satellite technology, artificial intelligence and cloud computing to derive insights on the health of natural ecosystems.
Are you smart, gritty and exude a can-do attitude? Do you want to contribute your AI skills to build a visionary tool to make the World more sustainable? Then apply to Earth.Org. We are seeking a entrepreneurial machine learning graduate to join a young and dynamic team in Hong Kong.
TASKS & DUTIES
- Develop algorithms for image machine processing able to detect patterns across vast amounts of satellite image data
- Help the team correlate chromatic changes to environmental indicators
- Ability to project results onto GIS maps
- Degree in Computer Science with demonstrable experience in machine learning techniques applied to image processing or computer vision
- Degrees in other related fields, including advanced mathematics, physics, and artificial intelligence will be considered as long as they accompany an advanced understanding of machine learning techniques
- Previous experience in working with remote-sensing technology a definite plus
- Technical familiarity with Geographic Information Systems (GIS) is desirable
- Ability to work with remote sensing specialists and have experience with frequentist and Baysesian statistics is a plus
- Experience with R, Python, Java Script, Bash is highly desirable
- Candidates with experience running multiple machine learning model ensembles, using a variety of gradient boosting, neural networks, random forests and variations on linear regressions will be preferred
- Spatial extrapolations will be essential, including variations of Kriging, Universal Kriging etc…
- Excellent command of the English language is essential
- Proven ability to work under pressure in a multicultural, multi-site environment
To apply please use the form below along with expected salary and availability.
Job Types: Full-time, Contract, Permanent