Research Associate/Applied Statistician: Integration and validation of eBird and BBS data to provide spatially explicit population trends

Key Skills

Effective communication skills, Machine learning techniques, R Programming, Statistical modeling

Job Description

Position Function

We seek an Applied Statistician to work as a Research Associate to lead the development and advancement of methods in machine learning and causal analysis to integrate data from the North American Breeding Bird Survey (BBS), a long-term volunteer survey run by the USGS, and from eBird, a popular citizen science project run by the Cornell Lab of Ornithology, to produce spatially explicit estimates of population trends and trajectories for > 400 bird species. The successful candidate will formally evaluate the complementarity of both data sets under a rigorous framework, and develop the methodology needed to extend the double machine learning framework (DML) currently used to estimate trends from eBird data. This project is a partnership with researchers at the Cornell Lab of Ornithology, Cornell University, and the US Fish and Wildlife Service. The Research Associate will be advised by Dr. Daniel Fink, Dr. Viviana Ruiz Gutierrez, and Dr. Orin Robinson in the Center for Avian Population Studies.

Project objectives include:

• Develop the methodology to assess the strengths and complementarity of BBS and eBird surveys.
• Develop the extension of the DML trend model used for eBird trend analysis to incorporate data collected under multiple distinct protocols.
• Develop the workflows and methodology needed to generate estimates of the interannual rate of change in species’ populations, i.e., population trends, across species ranges within the continental United States at a 27km2 spatial scale for a select set of species of management relevance and/or priority locations and create workflows to answer specific questions of interest.
• Validate the results from the integrated DML trend using a variety of methods such as simulation, comparison with estimates from independent data sets, comparison with estimates from non-integrated DML models.

In addition to leading this collaborative project with external partners, the Research Associate will work closely with scientists in the Conservation Science and the Status and Trends programs within CAPS. We encourage Research Associates to lead other aspects of related research questions and contribute to projects conducted in CAPS and with partners.

Anticipated Division of Time

• Lead the development of methods and workflows for the DML trends model that will integrate multiple data sources to provide trend information and population trajectories at fine spatial scale across the ranges of many species. Expected to contribute to proposals related to this work (55%).
• Present results at professional meetings, conferences, and popular seminars. Prepare peer reviewed papers and other research products, including reports and relevant information to partners. (25%)
• Engage in ongoing academic and intellectual life within the Conservation Science and Information Science Programs at the Lab of Ornithology, other programs at the Lab, Cornell University, and with all external partners. (10%)
• Participate in general project management and working directly with internal and external project collaborators. (5%)
• Perform related projects and special duties as assigned. Establish and maintain a safe, productive, and respectful working environment that fosters a culture of inclusivity and teamwork. Create and promote an environment that fosters diversity, equity, and inclusion in all endeavors. (5%)

Term of position

This is a two-year appointment, renewable for a third year contingent on funding, satisfactory performance, and available work.

Requirements

• PhD in computer science or applied statistics, with a strong background in machine learning, interpretable ML methods, geospatial data, handling and analyzing large data sets, and model development.
• Experience with R and other statistical languages.
• Ability to develop quantitative methods to answer ecological questions or hypotheses.
• Record of success conducting research and scholarly activities, including professional record of regularly publishing in peer-reviewed journals.
• Strong record of successfully meeting schedules and milestones of research projects that involve multiple stages and several participants.
• Demonstrated ability to simultaneously manage multiple ongoing research projects.
• Experience writing and/or administering grants to fund research.

Desired qualifications.

• Experience in causal analysis is preferred but not required.
• Experience related to using wildlife survey data and citizen science data is preferred but not required.
• Experience in ornithology is a bonus, but not required.

Supervision Exercised

Formal supervision of undergraduate student workers and academic supervision of undergraduate independent study research students annually. Training of staff, undergraduates, graduate students, postdocs, and visiting scholars.

To apply:

Please apply via Academic Jobs Online (https://academicjobsonline.org/ajo/jobs/27089).

Qualified candidates should submit a short cover letter, curriculum vitae, contact information for three references, and a statement supporting diverse communities (this can be a stand-alone document (preferred) or the information can be embedded in other parts of the application materials) outlining how, through research, teaching, service, mentoring, extension, and/or outreach, the candidate has and will contribute to support Cornell’s historical mission of “any person … any study,” via the website.

Applications will be reviewed as received, continuing until a suitable applicant is identified.

CALS hiring range for this position is $49,100 - $80,000.