Remote Crop Physiologist: Yield Optimization Expert

Placements24; Upington; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Health insurance

Retirement plan

Paid time off

Professional development

Job summary

Placements24 is seeking a Remote Crop Physiologist to join a fully remote team. You will leverage crop physiology expertise to model responses, optimize yield, and improve resource use efficiency on a global scale.

Collaborate with international researchers, design experiments, and develop quantitative models using R or Python. A Ph.D. in Crop Physiology or related field with 5+ years postdoctoral experience is preferred; strong scientific writing and remote-work capability are essential.

Qualifications

• PhD in crop physiology or related field with strong quantitative focus.
• Minimum 5 years post-doctoral experience in crop physiology and yield optimization.
• Proven ability to model physiological processes and analyze complex data.

Responsibilities

• Investigate and model crop physiological responses to environmental factors.
• Analyze field and controlled environment data to identify yield-limiting factors.
• Develop quantitative models to predict crop performance and optimize management.
• Collaborate with breeders, agronomists and data scientists to apply insights.
• Design experiments to enhance drought tolerance and nutrient use efficiency.
• Prepare scientific reports and presentations for stakeholders.

Skills

Post-doctoral research experience

Quantitative data analysis

Statistical modeling

Remote collaboration

Scientific writing

Education

Ph.D. in Crop Physiology / Plant Science / Agronomy

Tools

R

Python

Phenotyping data analysis

Job description

Placements24 is seeking a Remote Crop Physiologist to join a fully remote team. You will leverage crop physiology expertise to model responses, optimize yield, and improve resource use efficiency on a global scale.

Collaborate with international researchers, design experiments, and develop quantitative models using R or Python. A Ph.D. in Crop Physiology or related field with 5+ years postdoctoral experience is preferred; strong scientific writing and remote-work capability are essential.