60 Long Term Ecological Research Jobs Hiring Near You

Overview

The Department of Environmental Sciences at the University of Virginia (UVA) invites applications for a Research Scientist (Information Manager) to lead information and data management for the Virginia Coast Reserve Long Term Ecological Research project (VCR LTER).

VCR LTER is an interdisciplinary environmental research program based at UVA and supported by the National Science Foundation (NSF) since 1987 to advance knowledge of coastal ecosystems and their responses to long-term change. As part of the LTER Network—one of the longest-running ecological research networks in the world—VCR LTER generates long-term datasets that advance understanding of ecological dynamics in a complex coastal landscape. The Information Manager (IM) plays a central role in supporting discovery, synthesis, and long-term stewardship of these data. The IM is a core member of the VCR LTER team, working closely with faculty, postdoctoral researchers, graduate students, and collaborators across multiple institutions to ensure that data are well-documented, high-quality, accessible, and reusable—both within the project and across the broader ecological research community.

Location: This is a full-time position based at UVA in Charlottesville, VA, with periodic travel required to the VCR LTER site at UVA’s Coastal Research Center on Virginia’s Eastern Shore.

About the role: The VCR LTER IM (Research Scientist) oversees the full lifecycle of diverse ecological data, from acquisition and quality control through documentation, standardization, publication, and preservation. A main priority is stewardship of core LTER datasets such as long-term biological, oceanographic, hydrologic, geologic, and meteorological data. In addition, the IM serves as a collaborator and advisor—helping researchers design effective data workflows, harmonize data to support synthesis and modeling efforts, and translate information management best practices into practical, researcher-friendly solutions.

We are especially interested in candidates who understand the value of ecological data as observations of organisms, processes, and environments, and who appreciate how careful data stewardship enables discovery and research productivity across time and disciplines.

Key responsibilities

1. Data stewardship and publication
   • Manage, curate, and archive VCR LTER datasets and associated metadata.
   • Ensure compliance with federal and LTER data management requirements, including timely public data release.
   • Publish datasets to the Environmental Data Initiative (EDI), maintain accessible data catalogs on the VCR LTER website, and coordinate deposition in national repositories (e.g., NSF Public Access Repository, Biological and Chemical Oceanography Data Management Office).
   • Develop and maintain QA/QC workflows and ensure compliance with data documentation standards.
2. Systems, workflows, and infrastructure
   • Maintain and enhance data management systems supporting long-term field observations, sensor data, and derived data and modeling products.
   • Work with existing infrastructure (e.g., data servers, relational databases, automated workflows, web services, backup systems) to maintain continuity while contributing to thoughtful modernization over time.
   • Develop reproducible data processing pipelines using scripting and workflow tools.
   • Provide technical oversight for long-term deployed sensor instruments and data acquisition systems, including system configuration, integration, and advanced troubleshooting. Coordinate with field-station staff responsible for routine deployment and maintenance; periodic travel to field sites is required.
   • Coordinate with UVA Information Technology Services and project partners on system reliability and security.
   • Maintain the VCR LTER website, including programming web services for researchers, such as calendar and reservation systems.
3. Research collaboration and training
   • Work directly with faculty, postdocs, students, and staff to support data organization, documentation, and analysis.
   • Provide training and guidance on data management best practices and reproducible workflows.
   • Assist with data access, integration, synthesis, and modeling where appropriate.
   • Help researchers evaluate and apply advanced artificial intelligence (AI) tools to support research and information management.
   • Contribute to project reports, proposals, and publications related to information management. Maintain internal and external personnel and project databases.
4. Network engagement and professional development
   • Represent VCR LTER within the LTER Network and communicate effectively with Information Managers at other LTER sites.
   • Participate in national meetings, working groups, and professional development activities.
   • Engage with evolving community standards for ecological data and open science.

Qualifications

DEGREE REQUIREMENTS: Requires a doctoral degree or a master’s degree with significant experience, in ecology, environmental science, data science, computer science, information science, or a related field, by the start date.

Required experience/skills:

• Experience working across the research data lifecycle, including data cleaning, quality control, documentation, and publication.
• Proficiency in at least one scientific programming language (e.g., R or Python).
• Experience managing or working with structured datasets and relational databases (e.g., SQL).
• Strong organizational skills and attention to detail.
• Excellent written and verbal communication skills, with the ability to work effectively with scientists across disciplines, institutions, and career stages.

Preferred experience/skills:

• Ability to navigate and coordinate complex systems and find efficient solutions to challenging problems.
• Background or training in ecology, environmental science, or related natural sciences, or demonstrated experience working closely with ecological or environmental data.
• Familiarity with long-term observational or experimental datasets, sensor data, or field-based data collection.
• Interest or experience in field sensors and networks, from development and installation to maintenance and troubleshooting, including familiarity with basic electrical systems.
• Experience with metadata standards (e.g., Ecological Metadata Language).
• Familiarity with Geographic Information Systems (GIS) and their use for processing, analyzing, and archiving data.
• Interest in data synthesis, modeling, or advanced analytical workflows.
• Experience training or mentoring students or researchers.

Application process

TO APPLY: Apply online at https://jobs.virginia.edu/us and search for R0082043. Attach the following documents:

• A cover letter describing your motivation, experience, and qualifications for the advertised position.
• A resume or curriculum vitae.
• Contact information for three individuals who can provide professional reference letters upon request.

Please note that multiple documents can be uploaded in the application system.

Application details

APPLICATION DEADLINE: Review of applications will begin on May 1, 2026, but the position will remain open until filled. The University will perform background checks on all new hires prior to employment.

The preferred start date is September 1, 2026, but it is negotiable. This is a one-year appointment, and the appointment may be renewed contingent upon available funding and satisfactory performance.

For further information about the position, please contact Dr. Max Castorani, Associate Professor, at castorani@virginia.edu.

For questions regarding the application process, contact Rich Haverstrom, Academic Recruiter, at rkh6j@virginia.edu.

For more information on the benefits available to Research Scientists at UVA, visit hr.virginia.edu/benefits.

The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA’s commitment to non-discrimination and equal opportunity employment.