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Honing in on our inaugural program areas
DSE began as a broad vision to utilize data for making a positive impact on environmental challenges. Our funders and founding team were united by an optimism for our planet's health and the pressing need to use everything at our disposal to counter our climate uncertain future. They saw a clear path to leverage current research and expertise and use data to uncover insights for action. Underlying our efforts are open practices - open data, open science, and open source to create work that can be transparent, scalable, easily accessible, and designed with community support.
[Closed] We are Hiring! Schmidt DSE seeks a Research Software Engineer / Data Scientist
The Eric and Wendy Schmidt Center for Data Science & Environment at Berkeley (DSE) seeks a Research Software Engineer / Data Scientist with a passion for using creative coding methods to help develop and implement visualizations and other interactive data-enabled solutions who would be excited to see their work have an impact on the challenges facing our environment.
Incentivizing Regenerative Agriculture Practices
Diversified agricultural practices can function as both mechanisms of climate harm reduction and drivers of agricultural climate resilience. UC Berkeley Agroecology (Dr.
National Park Service Climate Change Decision Support
Management strategies in the National Park Service (NPS) have historically focused on conservation and restoration efforts, but in the face of increasing climate pressure, managers are increasingly forced to prioritize their resource use.
NOAA Alaska Fisheries API and Data Visualization Tool
Python-based toolset for working with public bottom trawl surveys data from the NOAA Alaska Fisheries Science Center Groundfish Assessment Program (NOAA AFSC GAP). This provides information about where certain species were seen and when under what conditions, information useful for research in ocean health and fisheries management.
Estimation of Snowpack Snow Water Equivalent from Remotely Sensed Data
In a time when erratic snowpack and pervasive flooding endangers global communities and livelihoods, estimation of the hydrological implications of snowpack, particularly Snow Water Equivalent (SWE), has major implications for the prediction of flooding intensity and timing, and for water system management.
Giulia Zarpellon
Giulia worked with DSE as a Data Scientist passionate about interrogating data in search of both meaningful questions and actionable answers.
Exploring Wildfire Data and Tooling
The impacts of climate change are fueling an alarming rise in the scale and frequency of wildfires. At DSE, we are interested in understanding the data and software infrastructure that researchers use to access open fire data and tooling.