Postdoc: Transforming Soil Carbon & Climate Modeling

Lawrence Berkeley National Laboratory; Berkeley (CA); On-site; USD 72,000 - 93,000; Full time

Job summary

Lawrence Berkeley National Laboratory in Berkeley, CA seeks a postdoctoral scientist to join an international group analyzing deep soil warming experiments. You will apply mechanistic and machine learning models to study warming effects on soil carbon cycling and estimate potential soil carbon feedbacks with climate.

The role emphasizes collaboration with scientists from graduate students to senior researchers, and work with colleagues at the University of Michigan.

Qualifications

• Scientific background in Earth system science with knowledge of terrestrial ecosystem ecology and soil science.
• Strong numerical modeling skills.
• Ability to design model experiments, visualize large data sets, and analyze results.
• Demonstrated ability to develop and deliver oral and written presentations of results.
• Record of scientific publications.

Responsibilities

• Synthesize observations from global soil warming experiments to inform model structure, calibration, and testing.
• Design and carry out model-based experiments, using model simulations to explore questions regarding the role of soils in terrestrial responses to global change, including soil carbon dynamics and CO2 exchange with the atmosphere.
• Improve and apply mechanistic and machine learning models for terrestrial processes.
• Evaluate biogeochemical interactions and their effects on carbon and energy exchanges with the atmosphere.
• Work creatively, independently, and productively.
• Work as a member of a large multidisciplinary research team.
• Author peer-reviewed journal articles and present work at conferences and meetings.

Skills

Numerical modeling

Data visualization

Scientific publications

Oral and written communication

Job description

Lawrence Berkeley National Laboratory in Berkeley, CA seeks a postdoctoral scientist to join an international group analyzing deep soil warming experiments. You will apply mechanistic and machine learning models to study warming effects on soil carbon cycling and estimate potential soil carbon feedbacks with climate.

The role emphasizes collaboration with scientists from graduate students to senior researchers, and work with colleagues at the University of Michigan.