Post Doctoral Fellow in Learning-based Control for Controlled Environment Agriculture (Mechanical Engineering)

Description

Velni Lab in the Department of Mechanical Engineering at Clemson University invites applications for a Post Doctoral Fellow position. This is a full-time appointment, with main duties of conducting research, writing technical papers, assisting in proposal development, and other duties as assigned.

Specific requirements: The assigned work entails developing new learning-based algorithms and tools to control the environmental conditions (in particular, lighting and CO2) in greenhouses. The applicants are expected to have prior knowledge of automation, control and AI applications in controlled environment agriculture demonstrated by prior publications. Strong and fundamental knowledge of plant sciences, as well as computational sciences (e.g., controls and machine learning) are required. Prior hands-on experience in greenhouses or plant factories is desired.

Qualifications

Ph.D. in Mechanical Engineering, Electrical Engineering, Agricultural Engineering, or a related field

Application Instructions

Applications, including a cover letter, full CV (including Google Scholar link), unofficial undergraduate and graduate transcripts, and names and contact info for three references, should be submitted through Interfolio (https://apply.interfolio.com/169674)

Equal Employment Opportunity Statement

Clemson University is an EEO/AA employer. Employment decisions are made without regard to characteristics protected by applicable law including disability and protected veteran status.