AI-Driven Phenomics Postdoctoral Scientist

Iowa Ag; Des Moines (IA); Vor Ort; USD 70.000 - 95.000; Vollzeit

Zusammenfassung

Vylor in Des Moines, IA is seeking a highly motivated Precision Phenotyping Postdoctoral Scientist to advance AI-enabled plant breeding through multimodal phenomics. The role focuses on predicting corn yield and agronomic performance from large-scale sensing data and genomic information.

You will develop and evaluate novel phenomic features, train transformer-based models, and build scalable pipelines across multiple environments while collaborating with breeders, data scientists, and software

Qualifikationen

• PhD required or imminent in plant biology, computer science, genetics, data science, or related field.
• Strong publication record and experience handling large-scale phenotyping data.
• Proven ability to develop and evaluate ML models for biological prediction tasks.

Aufgaben

• Collaborate on multimodal AI-driven prediction of corn yield, agronomic performance, and breeding outcomes.
• Develop and evaluate phenomic features from RGB, LiDAR, hyperspectral, multispectral, thermal, environmental, and genomic data.
• Design, train, and validate ML models including transformer-based architectures for agricultural prediction tasks.
• Build scalable data processing and model training pipelines for long-term phenotyping datasets across years and locations.
• Collaborate with breeders, geneticists, data scientists, and engineers to translate research into breeding solutions.
• Publish findings and contribute to IP while communicating results to technical and business stakeholders.

Kenntnisse

Machine learning

Deep learning

Multimodal data

Computer vision

Python

Ausbildung

PhD in a relevant field

Tools

PyTorch

TensorFlow

JAX

AWS

Jobbeschreibung

Vylor in Des Moines, IA is seeking a highly motivated Precision Phenotyping Postdoctoral Scientist to advance AI-enabled plant breeding through multimodal phenomics. The role focuses on predicting corn yield and agronomic performance from large-scale sensing data and genomic information.

You will develop and evaluate novel phenomic features, train transformer-based models, and build scalable pipelines across multiple environments while collaborating with breeders, data scientists, and software