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Stanford University

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Postdoctoral Research Fellow in Deep Learning, Remote Sensing, and Vector-Borne Disease Mapping Stanford University in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

One-year postdoctoral appointment with possibility of extension. The position pays the Stanford University required minimum for postdoctoral scholars; the FY27 minimum base pay is $79,056.

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Country

United States

University

Stanford University

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Keywords

Computer Science
Environmental Science
Deep Learning
Biology
Remote Sensing
Geography
Spatial Analysis
Computer Vision
Salud Pública
Disease Ecology
Statistics
ML

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About this position

Stanford University is advertising a Postdoctoral Research Fellow position with faculty mentor Joelle Rosser in the Stanford School of Medicine, within Medicine, Infectious Diseases & Geographic Medicine.

The project focuses on precision mapping of vector-borne diseases using deep learning and high-resolution remote sensing data. The fellow will help develop and validate computer vision models to classify mosquito breeding habitat from very high-resolution satellite and UAV imagery, build habitat suitability models, and study environmental drivers of arbovirus transmission. The work is interdisciplinary and combines disease ecology, geospatial analysis, spatial data science, machine learning, and environmental health.

The position is based at Stanford University, United States, and is intended for a recent PhD graduate interested in cross-disciplinary collaboration. The fellow will work with faculty and research staff, analyze geospatial datasets, optimize UAV imaging data collection, and lead manuscript preparation. There may also be opportunities to collaborate with partners across Stanford and with domestic and international research collaborators.

Eligibility highlights: completed PhD; strong background in disease ecology, habitat suitability modeling, remote sensing, geospatial analysis, or computer vision/deep learning; quantitative skills in spatial data analysis, data management, statistics, and machine learning; experience with R and Python is preferred, along with drone/SkySat/PlanetLab/Sentinel-2 data.

Funding: one-year appointment with possible extension; salary at least the Stanford required minimum for postdoctoral scholars (FY27 minimum base pay: $79,056).

How to apply: email a CV, cover letter, and two professional references to Kavita Coombe at [email protected] using the specified subject line.

Funding details

One-year postdoctoral appointment with possibility of extension. The position pays the Stanford University required minimum for postdoctoral scholars; the FY27 minimum base pay is $79,056.

What's required

Applicants must have completed a Ph.D. with substantial emphasis on disease ecology, habitat suitability modeling, computer vision deep learning algorithm development, remote sensing, or geospatial analysis. Preferred backgrounds include ecology, environmental science, climatology, geography, geophysics, computer science, or related fields. Strong quantitative skills are required, including graduate-level knowledge of spatial data analysis, data management, statistics, and machine learning/computer vision. Experience with drone, SkySat, PlanetLab, and/or Sentinel-2 data, R, Python, and disease ecology modeling will be viewed favorably.

How to apply

Email your application materials to Kavita Coombe at [email protected] with the subject line "YOUR LAST NAME Postdoc App for Rosser Lab 2026". Include a CV, a cover letter describing your research background and interests, and two professional references with contact information.

More information can be found here

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