The Ecosystem Services Program at the Nicholas Institute is seeking a student for Spring 2025 to support our assessment of nature-based solution projects’ effectiveness. The student project will focus on exploring the potential of artificial intelligence (AI) tools to enhance data accessibility.
Nature-based solutions protect, restore, or manage natural or semi-natural ecosystems to help nature and people adapt to climate change. With growing interest in using nature-based solutions to reduce impacts from natural hazards (like flooding), it is essential to understand their effectiveness. We recently identified limitations of publicly accessible databases on nature-based solutions projects, including gaps in project outcome reporting, inconsistent project categorization, and missing project design information. While critical project details often exist in design documentation and monitoring reports, they are generally inaccessible for large-scale analysis.
Artificial intelligence and machine learning may provide a way to automate the extraction of relevant data from various documents to populate a database of project details and outcomes. This position will assess the feasibility of using AI tools for this purpose by examining available project documentation, evaluating commercially available AI tools, and exploring options for customized open-source solutions where needed.
The student will report to senior policy associate Katie Warnell under the guidance of program director Lydia Olander. The student may also work with faculty and student collaborators at Duke and external collaborators. This is a part-time (8-10 hours/week), paid position for spring semester 2025. Work will likely be conducted in a hybrid model, with a combination of remote work and regular in-person meetings. Fully in-person work is also an option based on student preference.
Depending on the outcomes of this assessment, there may be an opportunity to continue with this work and implement identified solutions.
Key tasks
- Gather examples of project design documents, monitoring reports, and other resources
- Assess these resources’ potential for manual or automated information extraction
- Review commercially available AI tools for their capabilities, limitations, input requirements, and costs related to automated extraction of information from written resources to a database format
- Conduct pilot tests of promising tools to further explore their abilities and limitations
- If needed, explore open-source AI and deep learning tools for customized solutions to fill gaps of commercially available tools
- Consult with subject matter experts throughout this process for input and feedback
- Draft a report on the feasibility of using AI tools for extracting and organizing project data
Skills
- Computer programming, including familiarity with the use of APIs.
- Background in artificial intelligence / machine learning, natural language processing, and deep learning
- Experience applying open-source deep learning tools
- Interest in nature-based solutions, ecological restoration, and project evaluation
To apply
This position is open to students enrolled at Duke University. To apply, please send your resume, a cover letter, and a list of relevant courses you’ve taken to Katie Warnell, katie.warnell@duke.edu. Relevant courses include courses in machine learning (e.g. COMPSCI 571D, ECE580, ECE682D, STA 561D, IDS705), deep learning (e.g. ECE 685D, COMPSCI 675D), and natural language processing (e.g. ECE 684, COMPSCI 572). Coursework or experience programming is also required. We will begin interviews on 11/20/24 on a rolling basis.
The intent of this job description is to provide a representative and level of the types of duties and responsibilities that will be required of positions given this title and shall not be construed as a declaration of the total of the specific duties and responsibilities of any particular position. Employees may be directed to perform job-related tasks other than those specifically presented in this description.
Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.
Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas-an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.