University of Florida
Postdoctoral Associate Position in artificial intelligence, machine learning and crop modeling to improve crop nutrient management and ecosystem services. https://explore.jobs.ufl.edu/en-us/job/522135


Florida agriculture is a main provider of fresh produce of high nutritional value to the growing US population. Growers use genetic and management technologies to increase agroecosystems productivity while minimizing environmental externalities due to the use of fertilizers. Empirical approaches aimed at determining best fertilization practices by conducting field trials in a few locations and cultivars. However, the complexity and dynamics of agroecosystems prevent us from delivering on this ambition. Advances in complex systems science and artificial intelligence (AI) are creating opportunities to evolve agricultural practices to balance the needs of producers and consumers with reduced environmental impacts and improved conservation of resources.

As a postdoc, you will be expected to (1) develop a consistent data collection framework for agricultural field trials to enable current and future AI efforts; (2) contribute to the development of artificial intelligence (AI) algorithms that combine dynamic crop models and statistical machine learning methodology; and (3) apply AI models to aid in crop nutrient recommendations for nitrogen and phosphorus, balancing productivity with environmental impact.

Expectations include working with cross-disciplinary teams for model development; preparing data reports and presentations for scientific and industry groups; publishing results in peer-reviewed journals; and support in the mentoring of students.

As part of a post-doctoral experience, we offer opportunities and will encourage to participate and grow in research, teaching, grant writing, extension, and mentoring, all essential areas needed for the next step in your career.

AI-HARVEST (AI-Hub for Agricultural Reporting and Verification of Ecosystem Services through Sensing Technologies ). AI-HARVEST is a multi-disciplinary team of students and faculty utilizing AI, machine learning (ML) and crop modeling to improve crop nutrient management and ecosystem services. The faculty working on this effort are Dr. Alina Zare (Herbert Wertheim College of Engineering, Electrical and Computer Engineering), Dr Lincoln Zotarelli and Dr. Carlos Messina (UF/IFAS, Horticultural Sciences); Dr. Kelly Morgan and Lakesh Sharma (UF, Soil, Water and Ecosystems Sciences), Dr. Christian Christensen (Hastings Ag. Ext. Center).
EXPECTED SALARY:

Commensurate with Education and Experience
MINIMUM REQUIREMENTS:

A doctorate in plant or environmental sciences, computer science, computer engineering, or related areas.

Demonstrated ability to analyze large datasets using Python, R, or other programming languages

Able to work in high performing teams

Committed to train junior scientists

Independent, self-motivated, well-organized, and critical thinker

Outstanding written and verbal communication skills

Candidates must also have a commitment to IFAS core values of excellence, diversity, global involvement, and accountability.
PREFERRED QUALIFICATIONS:

Familiarity with agroecosystems sciences, crop nutrient and management

Working knowledge in crop physiology and modeling

Understanding of machine learning algorithms and geospatial analysis

Experience implementing, training, and evaluating deep learning architectures
Application instructions: In order to be considered, please apply online at https://explore.jobs.ufl.edu/en-us/job/522135  Please include a cover letter explaining your specific interest in joining the AI-HARVEST team, CV, and names and contact information of three references along with your application. Competitive salary with full benefits. Equal Opportunity Employer. Women, Minorities, Veterans and Disabled Persons are encouraged to apply.