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Research Associate in Disease Ecology

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Academic Level:
Postdoc & Early Career

The Han lab at Cary Institute of Ecosystem Studies is seeking a Research Associate to engage in a variety of new and ongoing projects related to predictive analytics and modeling in disease ecology. This position is similar to a senior postdoctoral research scientist but with greater latitude to co-develop research, and to lead grant proposals as Principal Investigator through Cary Institute. The successful candidate will be an excellent team player with versatile computational skills, with strong interest in the effective communication of computational/ecological concepts and research findings. Research experience in disease ecology is preferred, and more generally, candidates should possess a deep interest in investigating and understanding complex systems through rigorous and creative analysis of diverse data types. Thus, strong data science skills and expertise in R is required. Previous experience with machine learning is preferred, and candidates with previous experience with machine learning, deep learning, and explainable AI approaches applied to sequence data, remote sensing data, and image data are especially encouraged to apply.

There is a preference for this position to be based in-person at Cary Institute of Ecosystem Studies in Millbrook, NY, but remote work options are negotiable. Competitive applicants will have completed their PhD in ecology, biology, statistics, or related fields.

This is a salaried, exempt, full time and fully benefitted position subject to annual renewal contingent on performance. Please visit our website to learn more about how to apply!

Application Deadline: 1/20/2023
Note: Most programs maintain a similar program cycle (including similar application deadlines) year after year. Click here to understand dates and deadlines on

Program Dates: 1/9/2023 - 1/20/2023

Participating Institution(s):
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Cary Institute of Ecosystem Studies (Lead)

Program Materials:
 • Postdoc Website this link takes you to a different website

This Program can be Described by:
Academic Disciplines:
Applied Mathematics
Artificial Intelligence
Bioinformatics & Genomics
Computational Sciences
Ecology & Evolution
Spatial/Geographic Information Systems
STEM Fields

Computational Ecology
Data Science
Ecological Modeling
Infectious Disease
Machine Vision & Learning
Mathematical Modelling
Pathogen Biology
Population Dynamics
Quantitative Ecology
Satellite Data

Learn More and Apply!

This program is funded by:
National Science Foundation (NSF)
National Institute of Health (NIH)

Page last updated 12/20/2022
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