Sustainable and Humane Food Systems Data Science Fellow, Stanford Law School
Stanford University

Job Info

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Sustainable and Humane Food Systems Data Science Fellow, Stanford Law School🔍School of Law, Stanford, California, United States📁Academic📅Aug 28, 2024 Post Date📅104424 Requisition #

The Environmental and Natural Resources Law & Policy (ENRLP) Program at Stanford Law School and the Climate and Energy Policy Program (CEPP) at Stanford's Woods Institute for the Environment invite applications for a Sustainable and Humane Food Systems Data Science Fellow. The Fellow will join a thriving community based at the Law School, reporting to the ENRLP Program Faculty Director and working with the leaders of CEPP within the Stanford Doerr School of Sustainability.

This full-time fellowship is crafted for early-career technical scholars with a strong interest in the intersection of domestic food systems, agricultural sector pollution and transparency, animal welfare, environmental justice, and equitable climate and energy policy design.The position offers a hands-on opportunity to help us launch a new initiative dedicated to promoting a sustainable, humane, and climate-friendly modern food system.The initiative will focus on policy-informed research and regulatory/legislative processes to improve outcomes for animals, the environment, and agriculturalists in California and beyond.It will build on Stanford's track record of policy engagement and deepen partnerships with community and policy stakeholders.

Initially, the new Fellow will work on sustainability issues raised by Confined Animal Feeding Operations, including water pollution, energy consumption, carbon management, zoonotic disease, and antibiotic resistance, bringing an evidence-based approach and an equity lens to these concerns. The fellow will analyze and visualize a variety of related spatial datasets, which may potentially include such datasets as satellite data, air and water quality data, and methane emissions data. A willingness to apply expertise to new policy-relevant questions is more important than deep, preexisting experience with these specific issues.Because the Sustainable and Humane Food Systems initiative is new, the Fellow will have an opportunity to shape its future direction beyond this initial work.

Applicants should have:

• A Ph.D. from an accredited college or university in geography, data science, statistics, remote sensing, or another appropriate field of physical, social, biological, or environmental science

• Strong academic credentials, excellent writing and editing abilities, interpersonal and teamwork skills, and a collaborative spirit

• A commitment to promoting equity, diversity, and inclusion within the workplace and a track record of community engagement and service.

• Strong organizational/management skills, attention to detail, self-motivation, and aptitude for working with students and diverse policy stakeholders

• Sound judgment and exceptional ethical standards in serving as a trusted source for evidence-based analysis and policy engagement

• Ability to create and analyze spatial datasets and perform geographic analysis of spatial data using GIS software such as ArcGIS Pro, ArcGIS, QGIS, etc.

Additional preferred skills and experience include:

• Experience creating interactive data visualizations

• Familiarity with cartography and design

• Experience working with large databases

• Experience with machine learning methods

• Ability to work with satellite data in conjunction with other spatial datasets

• Experience working across disciplines with subject matter experts to create actionable outputs

Applicants should submit a cover letter summarizing their interest in this position and relevant experience, a resume, a writing sample, a list of three professional references, and a transcript through http://stanfordcareers.stanford.edu/, referencing job number 104424. Applications should be submitted as soon as possible and will be considered on a rolling basis until the positions are filled.

This position is for a one-year fixed term, with possibility for renewal.The Fellow is expected to work primarily in person at Stanford Law School in order to interact with students and team members.

The expected base pay range for this position is $72,000-$80,000. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.

*Note: The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

*Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job.

*Stanford is an equal employment opportunity and 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, protected veteran status, or any other characteristic protected by law.

*Stanford Law School seeks to hire the best talent and to promote a safe and secure environment for all members of the university community and its property. To that end, new staff hires must successfully pass a background check prior to starting work at Stanford University.

Additional Information

• Schedule: Full-time
• Job Code: 1384
• Employee Status: Fixed-Term
• Grade: H99
• Department URL: http://www.law.stanford.edu/
• Requisition ID: 104424
• Work Arrangement : On Site

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