Inside Higher Ed
Post Doctoral Fellow in Learning-based Control for Controlled Environment Agricu
Inside Higher Ed, Clemson, South Carolina, United States, 29631
Post Doctoral Fellow in Learning-based Control for Controlled Environment Agriculture
Velni Lab in the Department of Mechanical Engineering at Clemson University invites applications for a full‑time Post Doctoral Fellow position. The appointment focuses on developing learning‑based algorithms and tools to control greenhouse environmental conditions, primarily lighting and CO₂.
Responsibilities
Conduct research on novel learning‑based control algorithms for greenhouse environments.
Write technical papers and present findings at academic conferences.
Assist in proposal development and secure research funding.
Collaborate with plant science and automation teams within the lab.
Qualifications
Ph.D. in Mechanical Engineering, Electrical Engineering, Agricultural Engineering, or a related field.
Prior knowledge of automation, control, and AI applications in controlled environment agriculture demonstrated by publications.
Strong foundational knowledge of plant sciences and computational sciences (controls and machine learning).
Hands‑on experience in greenhouses or plant factories is desired.
Location
EIB 134, Clemson University, Clemson, SC
Application Instructions
Submit a cover letter, full CV (including Google Scholar link), unofficial undergraduate and graduate transcripts, and names and contact information for three references through Interfolio at https://apply.interfolio.com/169674.
EEO 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.
#J-18808-Ljbffr
Responsibilities
Conduct research on novel learning‑based control algorithms for greenhouse environments.
Write technical papers and present findings at academic conferences.
Assist in proposal development and secure research funding.
Collaborate with plant science and automation teams within the lab.
Qualifications
Ph.D. in Mechanical Engineering, Electrical Engineering, Agricultural Engineering, or a related field.
Prior knowledge of automation, control, and AI applications in controlled environment agriculture demonstrated by publications.
Strong foundational knowledge of plant sciences and computational sciences (controls and machine learning).
Hands‑on experience in greenhouses or plant factories is desired.
Location
EIB 134, Clemson University, Clemson, SC
Application Instructions
Submit a cover letter, full CV (including Google Scholar link), unofficial undergraduate and graduate transcripts, and names and contact information for three references through Interfolio at https://apply.interfolio.com/169674.
EEO 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.
#J-18808-Ljbffr