Postdoctoral Associate
3 months ago
Academic Job Description
Soil and Crop Sciences Section
Postdoctoral Associate
The College of Agriculture and Life Sciences (CALS) is a pioneer of purpose-driven science and Cornell University’s second largest college. We work across disciplines to tackle the challenges of our time through world-renowned research, education, and outreach. The questions we probe and the answers we seek focus on three overlapping concerns: We believe that achieving next-generation scientific breakthroughs requires an understanding of the world’s complex, interlocking systems. We believe that access to nutritious food and a healthy environment is a fundamental human right. We believe that ensuring a prosperous global future depends on the ability to support local people and communities everywhere. By working in and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here in New York, across the nation, and around the world.
Position Function
This position will work on a DOE-funded project entitled "Amazon vs Congo: Understanding the Intercontinental Differences of Tropical Rainforests’ Responses to Climate Variability" under the supervision of Professor Ying Sun. The responsibilities of this position include synthesizing in-situ field measurements from collaborators (site PIs) in the Amazon and Congo basins, conducting machine learning-based causal inference analysis on the response of climate variability of carbon fluxes for both site and regional scales, and incorporating a novel model of solar-induced chlorophyll fluorescence (SIF) and photosynthesis into the ELM-FATES model. This Postdoctoral Associate will collaborate closely with scientists from Harvard University and Lawrence Berkeley National Lab, along with field scientists in Amazon and Congo basins.
Anticipated Division of Time
Lab Research: 60%
Field Research: 10%
Writing: 30%
Requirements
A PhD degree in Remote Sensing, Climate Science, Ecology, or Geosciences or related discipline is required. Preferences will be given to candidates with expertise in developing and performing climate model simulations and programing skills in Fortran, C, Matlab, NCL, R or Python. Candidates with experience in deep learning will be given special consideration.
Supervision Exercised
This position may supervise students.
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