Department Contact: Samantha Lish, 575-646-1726, slish@nmsu.edu
Internal or External Search: External - Open to all applicants
Advertising Summary: The Jornada Experimental Range is seeking applicants for a Senior Research Scientist with a Soil Science focus and expertise applying deep learning foundational models to predict soil properties. The candidate must demonstrate expertise in applying advanced machine learning to predict soil properties, Python and R programing, as well as advanced understanding of soil survey, ecology, and soil-vegetation relationships. The successful candidate will be expected to make a leading contribution to several sponsored projects seeking to advance the spatial prediction of U.S. Soil Survey’s land health and land management concepts. The selected candidate will work closely with colleagues in the Plant and Environmental Sciences department at New Mexico State University.
Position Details
Position Title: Research Scientist III
College/Division: Agricultural Experiment Station
Department: 317250-JORNADA EXPER RANGE HEADQUARTERS
Location: Remote
Offsite Location (if applicable):
Target Hourly/Salary Rate: Commensurate with qualifications.
Appointment Full-time Equivalency: 1.0
FLSA Status: Exempt
Bargaining Unit Announcement: This is NOT a bargaining unit position with American Federation of State, County & Municipal Employees (AFSCME).
Contingent Upon Funding: Contingent upon external funding
Standard Work Schedule: Standard (M-F, 8-5)
If Not a Standard Work Schedule:
Job Duties and Responsibilities: *** THIS IS AN INITIALLY A ONE YEAR APPOINTMENT WHICH MAY BE EXTENDED; CONTINGENT UPON EXTERNAL FUNDING***
Lead the development of workflows to spatially predict land potential (Ecological Site Groups) and land condition (Ecological States) for the Western US. Develop methods to integrate field monitoring data and remotely sensed estimates of land condition based on the land potential based on metrics of soil stability, hydrologic function, and biotic integrity. Use results to estimate the spatial distribution of the condition for select western U.S. watersheds and help federal partners develop a sustainable information system delivery and database infrastructure which can support watershed scale land health assessments. Interpret, organize, and coordinate scientific research assignments concerned with unique or controversial problems. Prepare, analyze and develop scientific publications, and present findings at local, national, and international meetings. Prepares grant proposals to obtain funding in support of research activities. Develop novel computational concepts and approaches as an individual researcher and act independently on technical matters, making authoritative decisions and recommendations that have a major impact on extensive scientific research activities and result in national and/or international recognition. Maintains currency of knowledge with respect to relevant state-of-the-art technology, equipment, and/or systems and lead in the organization, supervision and training of students and less experienced members of the project team.
Qualifications
Required Education and Experience:
Associate's Degree + 11 years of relevant experience or a Bachelor's degree + 9 years of relevant experience. Master's degree or higher preferred.
Equivalent Qualifications:
Preferred Qualifications:
PhD in Soil Science or related field.
Experience of making a leading academic contribution and undertaking independent research.
A track record of publication and presentation of research results in quality journals/conferences in the areas of soil prediction, machine learning, artificial intelligence, or databases.
Experience developing and deploying techniques using deep learning architectures with convolutional neural networks and vision transformer autoencoders.
Comprehensive and up-to-date knowledge of current issues and future directions within the wider subject area of Artificial Intelligence and Machine Learning.
Fluent and familiar with one or more of the following programming languages: R and Python.
Work experience with cloud services like AWS, Azure, or GCP
Special Certification/Licensure:
Working Conditions and Physical Effort
Environment: Work is normally performed in a typical interior/office work environment.
Physical Effort: No or very limited physical effort required.
Lifting Requirements: Requires handling of average-weight objects up to 10 pounds or some standing or walking.
Risk: No or very limited exposure to physical risk.