The Environmental Data Science Innovation and Impact Lab (ESIIL) within CIRES at the University of Colorado Boulder is seeking Postdoctoral Research Scholars to address pressing environmental challenges through innovative environmental data science (EDS). The goal is to foster a collaborative research community empowered by open data, infrastructure, cross-sector partnerships, team science, and engaged learning to produce innovative and/or applied environmental biology research.
Requirements
- Knowledge of open-source programming languages (e.g., R, Python).
- Commitment to Open Science (i.e., available and findable data, reproducible and transferable codes to run on public cyberinfrastructure and open publications) and Open Education.
- Experience with multi-source, big data gathering, curation, and publication.
- Experience and/or knowledge of innovative data and analytics (e.g., AI/ML models).
- Experience and/or knowledge of notebooks and cyberinfrastructure.
- Experience and/or knowledge of open-source tool development and publication.
Responsibilities
- Develop and implement an environmental data science project that uses open data, tools, and cyberinfrastructure to address frontier research questions in environmental biology.
- Use open or available spatial and temporal data in creative ways to develop a data-driven research project.
- Leverage cloud, or other high-performance computing, resources to harmonize and analyze big, complex environmental data, and/or develop open AI-based pipelines.
- Contribute to the open, reproducible science and education objectives of ESIIL, which include creating and publishing well-documented datasets and codes, FAIR-compliant code workflows, or other outputs that will serve the larger EDS community and other audiences.
- Effectively share research results with colleagues and the broader science community through peer-reviewed publications, presentations, and other science products.
- Work with the ESIIL team and network on collaborative projects, such as with working group(s), hackathon teams, or summit participants, to advance environmental data science.
Other
- Ph.D. in environmental, biological, social, computer science, or data science field (including but not limited to Biology, Ecology, Ecosystem Science, Forestry, Geography, Sociology, Psychology, Anthropology, Economics, Geoscience, Space Engineering, Computer Engineering, Math, Environmental Studies, Remote Sensing Science, etc.).
- Effective project management skills (e.g., self-directed, independent).
- Knowledge of ethical and reciprocal research practices.
- Collaborative spirit and comfort working in large collaborative teams.
- Willingness to collaborate and contribute within ESIIL working groups, hackathons, and/or summits.
