UC Merced招收博后 AI系统应用方向

详细链接&申请链接：https://aprecruit.ucmerced.edu/JPF01832

Position description

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.

Qualifications

Basic qualifications
Applicants are required to have a Ph.D. in Computer Engineering, Agricultural Engineering, Data Science or a related field. 
Additional qualifications
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).
Preferred qualifications
Applicants are preferred to have a strong background in deep learning systems and models. Additional publications in other areas will be a plus.