Digital Phenotyping Intern: Field Data & UAV Sensing

Bayer; Chesterfield (MO); Hybrid; USD 47,000 - 99,000; Full time

Benefits offered by this job

Health care

Retirement

PTO

Job summary

Bayer seeks a highly capable candidate for a hybrid role based in Chesterfield, Missouri, focused on collecting imagery and sensing data from field trials and integrating phenotyping insights. The position involves collaboration with Field Testing, Data Science, and Computer Vision teams to advance research goals.

The ideal candidate is pursuing an MS or PhD in a relevant field with UAV license eligibility, and strong knowledge of remote sensing and ML basics.

Qualifications

• Active MS or PhD candidate in data science, precision agriculture, or related field.
• FAA Part 107 license required or ability to obtain before start date.
• Strong knowledge of remote sensing technologies, including LiDAR, multispectral or hyperspectral technologies.
• Familiarity with agricultural research and field trial methodologies.
• Ability to work collaboratively across areas of expertise.

Responsibilities

• Collect imagery and sensing data from field trials using LiDAR and multispectral sensors.
• Collaborate with Field Testing and Data Science partners to integrate digital phenotyping insights.
• Support agronomic assessments using manual ground-truthing methods in addition to UAV/sensing data collection.
• Contribute to system and workflow improvements by applying creativity and problem-solving to large-scale data challenges.

Skills

Remote sensing

UAV operation knowledge

Data analysis

Team collaboration

Machine learning basics

Education

MS/PhD candidate in data science / precision agriculture

Tools

LiDAR

Hyperspectral sensors

UAV imaging

Cloud platforms (AWS/GCP/Azure)

Job description

Bayer seeks a highly capable candidate for a hybrid role based in Chesterfield, Missouri, focused on collecting imagery and sensing data from field trials and integrating phenotyping insights. The position involves collaboration with Field Testing, Data Science, and Computer Vision teams to advance research goals.

The ideal candidate is pursuing an MS or PhD in a relevant field with UAV license eligibility, and strong knowledge of remote sensing and ML basics.