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Graduate Assistantships

Each year, faculty fellows at the Center for Geospatial Analytics seek prospective students for graduate assistantships funded through external grants. Opportunities available for students applying for Fall 2025 admission to the Ph.D. program in Geospatial Analytics will be posted below as funding is confirmed.

Recruiting for Fall 2025

Note that all assistantships are funded at a minimum of $30,000 per year for four years, plus health insurance and tuition waiver. We also plan to admit a select number of students on internal program funding, who are matched with advisors and research projects during their first year. If you are interested in a specific assistantship, we strongly encourage you to be in touch with the relevant supervisor before applying to the program.

Supervisor: Daniela Jones

The IDEALS (Intelligent Data for Energy and Agriculture Logistics and Supply Chains) Lab at North Carolina State University seeks a creative, motivated Ph.D. student with an interest in collaborating with farmers and data analytics to join a team developing sustainable biomass supply systems.

The selected applicant will join a research group focused on applying several technologies in agriculture like intelligence frameworks, machine learning, hyperspectral satellite imagery, operations research, and geospatial analytics methods. The student will work with sweetpotato growers to create predictive models and tools that define post-harvest initial conditions based on field and growth information, incorporating both the insights of experienced employees and quantitative data.

Review of applications will begin immediately and continue until the position is filled. To apply, complete the application at grad.ncsu.edu/apply by February 1, 2025. Applicants should hold a degree in biological/agricultural engineering, industrial engineering, environmental science, agronomy, or a related discipline. Experience with GIS, remote sensing, and machine learning is desired.

For more information about the position, contact Dr. Daniela Jones (dsjones5@ncsu.edu) and include a copy of your CV.

Supervisor: Krishna Pacifici

Ph.D. student would develop a suite of integrated species distribution models (iSDMs) at multiple spatial scales for a range of federally listed aquatic species (fish, mussels, and amphibians) in the southeastern U.S. to inform recovery. This would include estimating environmental drivers of distribution and abundance and identifying areas of potential recovery actions. The student would work with a team of federal and state partners working in aquatic conservation and be expected to lead on modeling and decision support efforts. The student would have flexibility to explore a range of research questions related to hierarchical modeling, data integration, multi-species modeling, and decision support and be a part of the Quantitative Ecology Lab at NC State working with Dr. Krishna Pacifici.

Minimum Requirements/Qualifications:

  • B.S. and M.S. in fisheries, wildlife, ecology, conservation biology, statistics, or related fields.
  • Knowledge of GIS/geospatial analysis in R, statistics, and modeling with special emphasis on Bayesian hierarchical modeling and integrated modeling (IPMs/iSDMs/joint models preferred).
  • Excellent verbal and written communication skills.
  • Ability to work in an interdisciplinary research group.
  • Commitment to maintaining an inclusive work environment.

Highly Desirable:

  • Record of peer-reviewed publications
  • Proficiency with hierarchical modeling and data-integration either through existing software (JAGS/Nimble/Stan/TMB) or customizable methods
  • Spatial modeling experience (e.g., Spatial statistics, Spatial Capture-Recapture, GIS/QGIS/GRASS)
  • Experience working with and managing large heterogeneous data sets

Email a cover letter outlining interests and qualifications, CV, and names and contact information for three potential references as a single pdf document to Dr. Krishna Pacifici (jkpacifi@ncsu.edu) with the subject line “Aquatic SDMs PhD”. Review of applications will begin immediately and continue until a qualified candidate is identified. Please address any questions to Dr. Krishna Pacifici (jkpacifi@ncsu.edu).

Supervisor: Zhen Qu

Dr. Zhen Qu’s research group is seeking a Ph.D. student to work on predicting greenhouse gas emissions using multi-scale observations. The successful candidate will leverage machine learning, statistical analysis, and data on atmospheric composition, land cover, precipitation, groundwater, and other environmental variables to estimate the sources and evolution of carbon dioxide (CO2) and methane (CH4). Opportunities to contribute to additional research areas, such as air pollution modeling and environmental justice studies, are also available.

With growing attention and funding for greenhouse gas mitigation, this project seeks to harness big data, along with advanced machine learning and statistical methods, to deepen our understanding of climate change and greenhouse gas behavior. The outcomes are expected to significantly contribute to the Global Stocktake under the United Nations Framework Convention on Climate Change (UNFCCC).

Email Dr. Zhen Qu (zqu5@ncsu.edu) for more information.

Past Opportunities

Curious about what projects students have applied to work on in the past? Brief synopses are provided below:

  • Estimating Greenhouse Gas Emissions Using Satellite Observations — This project aims to combine big data with new machine learning and statistical techniques to advance our understanding of climate change and greenhouse gases. The successful candidate will apply machine learning, statistical analysis, supercomputer simulations, satellite data, and atmospheric simulations to estimate the sources and evolution of carbon dioxide (CO2) and methane (CH4).
  • Nutrient and Water Resources Modeling — The position will focus on modeling of nutrient flows and downstream water quality impacts. This position is associated with STEPS, a convergence research center focused on phosphorus sustainability.
  • Pest Spread Modeling — This position will focus on using the Pest or Pathogen Spread (PoPS) model to document dispersal patterns of corn earworm, a major pest of crops in the eastern United States. To do this, the candidate will leverage several decades of corn earworm trap data already collected to calibrate and validate a spread model for this pest. This model will simulate the reproduction, dispersal, and establishment of corn earworm over time to explore changes in population cycles due to both abiotic and biotic factors.
  • Geospatial Computation and A.I. — Developing novel and scalable AI, computer vision, and deep learning techniques for monitoring and mapping natural resources using multi-sensor global earth observations.
  • Land Change Modeling –– Join the Urban Systems Lab to model urban growth, future flood hazard and human adaptive response to flooding, with a focus on scenario-based land change modeling that considers human-flood interactions.
  • Ecological Impact of Oyster Restoration –– Students who have been historically underrepresented in the sciences (must be U.S. citizens/permanent residents) are invited to participate in research related to a large oyster restoration program. Potential projects include population modeling, benthic habitat studies and the use of active and passive underwater acoustic data to monitor marine species.
  • Atmospheric Chemistry Modeling –– Join the Qu Lab to develop a research project applying satellite remote sensing observations, atmospheric chemistry models and data assimilation and machine learning methods to estimate the sources and evolution of air pollutants and greenhouse gasses. The student can also be involved with analyzing environmental justice and regulation implications using the results.
  • Spatial Social Network Analysis for Disaster Recovery –– Join the Location Matters Lab as part of a research group focused on understanding environmental and disaster recovery policy implementation through social science frameworks. The student will be actively involved in collaborations with communities recovering from disaster and nonprofit and government organizations supporting social and ecological resilience.
  • Invasive Species Modeling –– Join the Biological Invasions Lab to mode invasive species spread and early detection using remote sensing and machine learning, with a focus on invasive pest and pathogen modeling using process-based models with machine learning or remote sensing with deep learning for early detection of pest and disease symptoms using high-resolution remote and aerial imagery.
  • Geospatial Analytics for Natural Resource Challenges –– Join the Land Change Lab as part of a research group to study conservation and natural resource management in parks and protected areas, including modeling fire and ecosystem processes at landscape levels, studying the impacts of development along park boundaries and building GIS support systems for the National Park Service.
  • Global Change and Forest Hydroecology –– Join the Watershed Ecology Lab as part of a research group focused on the dynamics of forest hydrologic cycling, from the stem to space, including field research, remote sensing and forest dynamics modeling. The student will be actively involved in collaborations with the US Forest Service.
  • Urban Conservation Biology –– Join the Youngsteadt Urban Ecology Lab to examine effects of urbanization and climate change on the crystal skipper butterfly. Field work is an important component of this position.
  • Climate Change, Carbon, and Phenology –– Join the Spatial Ecosystem Analytics Lab as part of a multi-institutional team investigating changes in vegetation phenology, the impact of those changes on carbon fluxes, and the effect of drought on ecosystems.
  • Aquatic Biogeochemistry and Geospatial Modeling –– Join the Osburn Lab as part of an interdisciplinary and multi-institutional team working to characterize natural and anthropogenic sources and distributions of dissolved organic nitrogen (DON) in coastal watersheds. The position will be a combination of laboratory and computation activities; limited opportunities for field work are possible.
  • Engaging Stakeholders in Flood Resilience Planning through Landscape Forecasting and Interactive Decision Analytics –– Join the Landscape Dynamics Lab to collaborate with an interdisciplinary team to co-envision an open source web based platform for stakeholder engagement and development of flood adaptation strategies. This platform will integrate scientific models to facilitate multi-way communication among stakeholders, decision-makers, and the research team.
  • Modeling Phosphorus Flows in Agricultural Landscapes –– Join the Biosystems Analytics Lab (Biological and Agricultural Engineering) and Obenour Lab (Civil, Construction, and Environmental Engineering) to join a project funded through the NSF STEPS Center at NC State.
  • Human Exposure to Air Pollution –– Join the Richmond-Bryant Lab to perform research through the Louisiana State University Superfund Research Program on Environmentally Persistent Free Radicals. The student will be part of an interdisciplinary and multi-institutional team working to characterize human exposure to air pollution emitted by an open-burn-open detonation hazardous waste facility (the only commercially permitted one of its kind in the U.S.) in a community with intersecting vulnerabilities.
  • Surface Water and Flooding Dynamics with Multi-sensor Time-series of Satellite imagery –– Join the Geospatial Analysis for Environmental Change Lab to answer questions pertaining to flooding and surface water dynamics through innovative use of remotely sensed imagery as part of interdisciplinary and multi-institutional team funded by NASA.
  • Building Capacity for Improved Citizen Science by Understanding the Racial-Spatial Bias in Environmental Data –– Join the Cooper Public Science Lab to explore multiple dimensions in the design and implementation of citizen science programs to address environmental injustices and public health challenges.
  • Large Scale Change Monitoring from Multisource Imagery –– Join the Spatial Ecosystem Analytics Lab to answer questions of broad significance through innovative use of remotely sensed imagery as part of an interdisciplinary and multi-institutional team building a system to monitor and characterize change over huge spatial scales using heterogeneous satellite imagery.
  • Hydro-Ecology and Forest Management for Global Change (two positions) –– Be part of collaborative project led by four faculty from the Center for Geospatial Analytics and Department of Forestry and Environmental Resources to study climate adaptive management for forest ecosystem services.
  • Analytics for Sustainable Agriculture –– Join the Biosystems Analytics Lab to leverage remotely sensed and in situ data to develop predictive and explanatory models for use in sustainable environmental and agricultural management.
  • Landscape Transformations –– Join the Dynamic Ecosystems and Landscapes Lab to research anthropogenic change and landscape transformations to improve landscape policy and management decisions.
  • Inequities in Built Environments & Active Living –– Join the C-WHERE lab to explore spatial energetics (space, place, human movement, physical activity) and how built environments influence active living, with a focus on righting inequities and bringing power to data.
  • Modeling the Spread of Infectious Swine Disease –– Join the Machado Lab to develop forecast models of swine diseases, focusing on the epidemiology of transboundary animal diseases, integrating approaches such as traditional spatiotemporal statistics for mapping disease spread and forecasting disease emergence in animal and human populations.
  • Carbon Cycles and Environmental Justice Policy –– Join the Ecohydrology and Watershed Science Laboratory to assess impacts of climate change and land use change on terrestrial water and carbon cycles and/or evaluating datasets and methodologies used for environmental justice policy.
  • Modeling the Spread of Invasive Species –– Join the Biological Invasions Lab join a research group focused on interactive near-term forecasting of landscape and environmental change, with emphasis on collaborating with stakeholders to explore what may happen in the future under different scenarios.
  • Remote Sensing of Geologic Hazards –– Join the Earth Surface Processes Lab to join a team of geoscientists combining field-based studies with geospatial analysis and modeling.
  • Landscape Connectivity Dynamics in Surface Water Networks — Join the Geospatial Analysis for Environmental Change Lab to investigate climate and land-use change effects on landscape connectivity dynamics.
  • Seasonality from Space — Join the Spatial Ecosystem Analytics Lab on a NASA-funded project investigating satellite data fusion and time series analysis.
  • Winter Weather — Join the Environment Analytics group to study the complex interactions within snow storms and wintery mix storms.
  • Modeling Forest and Water Resources under Changing Conditions — Join the Watershed Ecology lab group and combine various data sources to create projections of future landscape conditions.
  • Modeling Agricultural and Water Resource Dynamics — Join the Biosystems Analytics Lab to study the effects of global and local change on fresh and estuarine water quality, land-sea connectivity and agroecosystem productivity.
  • Surface Water Dynamics from Space — Join the Geospatial Analysis for Environmental Change Lab to investigate hydroclimatic drivers of surface water extent dynamics and advance quantification of water extent and volume.
  • Remote Sensing Forest Gap Dynamics — Join the Applied Remote Sensing and Analysis lab group to examine the role and influence of forest gaps in relation to localized large-scale disturbances.
  • Exploring Urban Planning Scenarios — Join a geovisualization research group focused on developing interactive online 3D visualization systems for innovative public engagement and urban planning in the Research Triangle Region of NC.
  • Natural Resource Management and Ecosystem Services — Focus on geospatial analytics for fire and natural resource management in national parks and protected areas, including modeling fire and ecosystem processes at landscape levels, forecasting development along park boundaries, and building decision support systems.
  • Sustainability Solutions with Land Change Science — Join an interdisciplinary team investigating the dynamics of urbanization and landscape change in the Southeast US through land-change modeling in collaboration with the US Geological Survey.
  • Outdoor Recreation Decision Support Systems — Join a research group focused on built environments and active living, and contribute to developing new decision support analytics for the Conservation and Outdoor Recreation Branch of the National Park Service.
  • Smart and Connected Communities — Join a team designing a publicly available, multi-user, online serious game called TomorrowNow to engage citizens and decision makers in developing collaborative scenarios of urbanization and stormwater management, as part of a new grant from the NSF Smart and Connected Communities program.
  • Biological Invasions and Plant Health — Join the Spatial Analytic Framework for Advanced Information Systems (SAFARIS) team to develop spatial models and techniques to forecast movement of invasive pests and pathogens affecting food security and natural ecosystems.
  • Participatory Video and Engaged Environmental Justice — Use participatory mapping and video methods to understand how communities address resource inequities in disaster recovery plans, as part of a larger research project focused on long-term recovery from Hurricane Matthew in NC.
  • Geospatial Social Networks of Environmental Governance — Examine changes in watershed governance following disasters with spatially-explicit social networks in order to understand how and why environmental governance transitions occur.
  • Seasonality from Space — Join a NASA-funded research project to generate moderate resolution land surface phenology from Landsat and Sentinel data fusion. Learn more.
  • Innovation in Local Government — Join a team developing solutions through geospatial visualizations and analytics for internal and external stakeholders of local government in partnership with Wake County, North Carolina.