The Berkeley Lab’s Climate and Ecosystem Sciences Division (CESD) welcomes applicants for a machine learning Postdoctoral Fellow position to study carbon intensity and accounting during biofuel feedstock production.
In this role, the successful candidate will be responsible for coordinating and integrating large temporal and spatial datasets collected by a diverse set of field teams working on multiple biofuel species, e.g. maize, sorghum, rice, across multiple climatic zones in the United States. The primary duty of the Postdoc Fellow is focused on big and diverse data analysis, integration and scaling using machine learning techniques, and implementing predictive ML based models for carbon intensity quantification during biofuel feedstock production. The successful candidate will work with a diverse group of field teams and across >10 sites under the SMARTFARM program of ARPA-E (Advanced Research Project Agency - Energy).
The position offers an excellent opportunity to work with an interdisciplinary team across multiple labs and universities under the SMARTFARM program. LBNL is a renowned center of scientific expertise in many facets of fundamental and applied sciences related to the environment and water resources.
What You Will Do:
- Work collaboratively with a diverse group of teams to ensure data collection and delivery is consistent and coordinated.
- QA/QC of the datasets, including climatic, soil, plant and flux data collected by the field teams.
- Develop and implement ML based algorithms for the analysis and integration of diverse datasets collected during biofuel feedstock growth.
- Analyze data and extract patterns and correlations using appropriate data mining methods.
- Conduct global sensitivity analysis, integration and scaling exercises across all sites.
- Author peer-reviewed conference or journal papers, 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.
- Demonstrated experience with traditional and deep machine learning methods.
- Theoretical understanding and application of data analysis methods such as statistical techniques, signal processing, pattern recognition, or data-informed modeling.
- Experience integrating large observational data sets from diverse sources, data curation and QA/QC.
What We Desire:
- Familiarity with libraries, frameworks, or workflow tools that enable data analytics and machine learning (e.g., NumPy, Pandas, Pytorch, Keras, Tensorflow, Jupyter Notebooks).
- Experience and knowledge with environmental, agriculture and biofuel datasets and research practices.
- Demonstrated record of publications or conference presentations.
- Interest in collaborative research, open science, and implementing maintainable and reusable software/data products for broader scientific use.
Requested Application Materials:
- Cover Letter/Research statement: Include a cover letter introducing yourself, your application, and describing your interest in the position.
- Curriculum Vitae/Resume: Either an academic CV or a resume is acceptable. Be sure to highlight technical skills, interests, and synergistic activities relevant to the position. Include links to software projects or public code repositories.
- References: Provide contact information for three professional references with whom we may communicate regarding your work and your application.
The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on February 28, 2021. To apply, go to https://lbl.referrals.selectminds.com/ , and search for position 91692
- This is a full time, M-F, exempt from overtime pay (monthly paid), 2 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 3 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.
Learn About Us:
Berkeley Lab (LBNL ) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 13 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.
Working at Berkeley Lab has many rewards including a competitive compensation program, excellent health and welfare programs, a retirement program that is second to none, and outstanding development opportunities. To view information about the many rewards that are offered at Berkeley Lab- Click Here.
Equal Employment Opportunity: Berkeley Lab is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status. Berkeley Lab is in compliance with the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4. Click here to view the poster and supplement: "Equal Employment Opportunity is the Law."
Lawrence Berkeley National Laboratory encourages applications from women, minorities, veterans, and other underrepresented groups presently considering scientific research careers.