Postdoctoral Scholar in Artificial Intelligence Systems and Applications

A full-time Postdoctoral Scholar position is available in Dr. Xiaoyi Lu's PADSYS Lab to investigate scalable system software for emerging applications such as precision agriculture, digital twins, deep learning, and so on. The Postdoc will also be focused on advancing agricultural food technology through the integration of artificial intelligence (AI). Specifically, the Postdoctoral Scholar is expected to conduct intellectual research involving parallel and distributed computing, system software design and development for AI and digital twin applications, energy efficiency optimization, and contribute to innovative research aimed at improving food production processes, enhancing food quality, developing sustainable agricultural practices, and developing data-driven strategies for sustainable agriculture. The Postdoctoral Scholar will work under the guidance of the PI, write research articles with the PI aimed at disseminating the obtained results from the research performed in the PADSYS Lab.

Responsibilities of this position will include:

AI and Data Analytics in Agriculture

* Machine learning models for pest and disease prediction

* Crop classification using multispectral imagery

* Digital twin models for farm simulation and management

* Collaborate with multidisciplinary teams, including researchers, industry partners, and stakeholders in the agricultural and food sectors.

* Conduct cutting-edge research on the applications of AI in agricultural food technology.

* Analyze and interpret research findings, and disseminate results through high-quality publications in peer-reviewed journals and presentations.

*Stay current with technological advancements in AI, and agricultural food

technology, and apply this knowledge to enhancing ongoing research initiatives.

AI and Data Analytics in Agriculture

* Mentor graduate students and undergraduate researchers in the lab.

Applicants are required to have a Ph.D. in Computer Engineering, Agricultural Engineering, Data Science or a related field.

Experience in one or more of the following: AI infrastructure, digital twins, deep learning systems and models, and distributed computing. Knowledge of sustainable agriculture practices and food systems. Excellent written and verbal communication skills, with a strong record of publications in relevant fields. The ideal candidate should have at least 1-2 peer-reviewed research papers published in prominent HPC venues (e.g., SC, IPDPS, TPDS).

Applicants are preferred to have a strong background in deep learning systems and models. Additional publications in other areas will be a plus.

• 3 required (contact information only)

The University of California, Merced, is the newest of the University of California system's 10 campuses. With over 9,000 undergraduate and graduate students (https://cie.ucmerced.edu/analytics-hub/student-statistics), UC Merced is committed to interdisciplinary excellence in research and teaching as well as to diversity, equity and inclusion. Ranked as one of the best public universities in the nation by U.S. News and World Report, UC Merced provides outstanding educational opportunities to highly qualified students from the heart of California, the nation, and abroad. The campus has special connections to nearby Yosemite National Park; is on the cutting edge of sustainability in construction and design; and supports the economic development of Central California. The Merced 2020 Project doubled the physical capacity of the campus, and enhanced academic distinction, student success, and research excellence (https://merced2020.ucmerced.edu/).

The University of California, Merced is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.

Please refer to the University of California's Affirmative Action Policy and the University of California's Anti-Discrimination Policy.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements. This includes the University of California Policy on Vaccination Programs: https://policy.ucop.edu/doc/5000695/VaccinationProgramsPolicy.