Massive opportunities exist for innovating AI technologies that accelerate our ability to achieve more precise and sustainable agriculture. Warming temperatures and associated increases in extreme weather events, including heat exposure, results in major economic losses, can cause a reduction in yield and quality of specialty crops, including grapevine. The UC Davis Rossi Postdoctoral fellow will join a multidisciplinary team focused on developing a low-cost, AI-enabled sensing kit that will be mounted on existing farm vehicles (e.g. tractors and ATVs) of collaborating growers in viticultural regions with high heat wave risk. This ground-based sensor provides a critical data stream that can be combined with aerial and satellite imagery, along with other data inputs, to dramatically expand the grape industry’s capacity to predict plant stress (e.g. water, nutrient, pathogen, etc.) as well as yield and berry chemistry in response to future climate conditions and extreme weather events. The Forrestel and Earles Labs, in collaboration with industry partners, are engaged in large-scale viticultural data collection efforts that provide an unprecedented dataset for innovating AI sensing and modeling frameworks in viticulture, and agricultural at large. Depending on the Scholar’s background and interest, there are opportunities to work on AI algorithm design and modeling, sensing kit development, and integrating data and model development that leverages data across scales and from several sources to predict yield and plant responses to extreme weather. The Earles and Forrestel Labs, UC Davis Departments of Viticulture & Enology and Biological & Agricultural Engineering, are looking for a diverse pool of applicants from biological, physical, and/or engineering backgrounds with applied or related experience in at least one of the following areas: biophysical modeling, deep learning algorithm development, computer vision, imaging hardware, sensing systems design, and/or robotics. We are interested in applicants who want to push the technological boundaries of agricultural AI; including edge hardware/compute, multiinput and multi-output modeling, model architecture development, and deep regression, among other emerging challenges in deep learning. The Scholar will work closely with a broader team of researchers focused on sensor testing, data collection/management, and deep learning algorithm development, along with world-class plant biologists studying grapevine responses to heatwaves. The Scholar will jointly work between the Forrestel and Earles Labs in Davis, California, to develop and deploy novel AI technologies to high climatic risk viticultural regions – massively expanding our capacity to monitor grapevine production at high spatio-temporal resolution. UC Davis and the Earles and Forrestel labs are dedicated to creating a working environment that promotes equity and justice for all people. We recognize that a diverse and equitable workplace with individuals having a multitude of identities perspective and experiences promotes greater innovation, productivity and a stronger community of scholars overall. We follow the guidelines outlined in the UC Davis Diversity, Equity and Inclusion Principles of Community and strongly encourage people of all background and identities to apply to this position.
Salary and Benefits The annual range of salary for this position ranges from $53,460 to $64,008 depending on experience. The initial appointment is at 100% for one year, with the possibility of extension based on satisfactory performance and availability of funds. The salary is commensurate with experience and is governed in part by contracts between the University of California and the postdoctoral union. The position will receive full benefits as outlined by the UC postdoctoral contract, including 24 days of paid time off (PTO) and 12 days of sick leave per year. More information on UC Davis Postdoctoral Scholar benefits can be found here: https://hr.ucdavis.edu/employees/benefits/postdoc-scholars.
Qualifications/Experience Potential qualifications or experience relevant to this position could include but are not limited to: • Ph.D. in quantitative biological, physical, or engineering discipline • Applied or related experience in at least one of the following areas: biophysical modeling, deep learning algorithm development, computer vision, imaging hardware, sensing systems design, and/or robotics • Coding in Python, shell, and/or C++ • Writing deep learning models using libraries such as PyTorch, Keras, or TensorFlow • Interest in developing rugged/reliable AI tools for challenging agricultural environments • 3D modeling, materials selection, prototyping, and fabrication
Application • A cover letter outlining your interest, expertise, and technical skills relevant to this position. • A curriculum vitae. • Copies of transcripts (unofficial acceptable with application) and a letter of degree conferral (if applicable). • Two copies of publications – including one first author peer reviewed paper – exemplary of your writing and your knowledge, skills, and abilities relevant to this position. • Contact information for three references, including name, current position, email, phone number, and relationship to you.
Please send your complete application package as a single PDF to email@example.com and firstname.lastname@example.org with AI Sensing Grape Heatwaves in the subject line. Applications will be reviewed on a rolling basis starting on December 15th, 2020.
The University of California 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. For the complete University of California nondiscrimination and affirmative action policy see: http://policy.ucop.edu/doc/4000376.