Earth Science Postdoc

Lawrence Berkeley National Lab’s (LBNL ) Climate & Ecosystems Division has an opening for a Earth Science Postdoc, developing a scaling construct for quantifying watershed heterogeneity and functioning across scales based on a suite of remote sensing data and data analytics (machine learning) tools. 

You will be associated with Berkeley Lab’s Watershed Function Scientific Focus Area (SFA) project (watershed.lb.gov). This project focuses on developing a predictive understanding of how mountainous watersheds retain and release water, nutrients, carbon, and metals. In particular, the SFA is developing understanding and tools – novel sensors and observation platforms, airborne remote sensing products, Earth system simulators –  to measure and predict how droughts, early snowmelt, and other perturbations impact downstream water availability and biogeochemical cycling at episodic to decadal timescales. 

In this exciting role, you will be responsible for synthesizing large temporal and spatial datasets from satellite/airborne remote sensing as well as bedrock-through-canopy datasets on water and nutrient cycling, ecohydrology and biogeochemistry in a mountainous watershed in the Upper Colorado River Basin. The primary task is focused on identifying co-variability among bedrock-to-canopy data layers, characterizing the spatiotemporal dynamics of mountainous ecosystems and biogeochemical functioning, and testing various scaling theories/methods. 

 

What You Will Do:

• Work collaboratively with a vibrant, large, multi-disciplinary, multi-institutional team to integrate diverse datasets for the spatiotemporal characterization of the watershed.
• Analyze data and extract patterns and correlations using appropriate data mining methods.
• Develop and implement machine learning based algorithms for integrating spatiotemporal datasets including remote sensing and ground-based measurements for watershed characterization.
• Developing a watershed-to-basin scaling construct that can be used to guide data acquisition and Earth systems model parameterization.
• Author peer-reviewed conference or journal papers, contribute to project products, and contribute to grant proposals.

 

What is Required:

• Ph.D. in Environmental Sciences/Engineering, Data Science, Applied Mathematics, Computer Science, or other related technical disciplines.
• Understanding of watershed hydrology, landscape evolution and ecosystem processes.
• Demonstrated experience with machine learning methods.
• Theoretical understanding and application of data analysis methods such as statistical techniques, signal processing, pattern recognition, or data-informed modeling. 

 

Desired Qualifications:

• Experience and knowledge with environmental, ecological and/or remote sensing datasets and research practices.
• Familiarity with libraries, frameworks, or workflow tools that enable data analytics and machine learning (e.g., NumPy, Pandas, Scikit-learn, Keras, Tensorflow, Jupyter Notebooks).
• Demonstrated record of publications and conference presentations.
• Interest in collaborative research, open science, and implementing maintainable and reusable software/data products for broader scientific use.

 

Notes:

• This is a full-time 1 year postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 4 years of paid postdoctoral experience.
• Salary for Postdoctoral positions depends on years of experience post-degree.
• This position is represented by a union for collective bargaining purposes.
• Salary will be predetermined based on postdoctoral step rates.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.
• Berkeley Labis located in an environment recognized for offering a high quality of life, having both abundant natural beauty and exciting urban surroundings.

 

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