Genomic AI Researcher - Deep Learning

Bayer CropScience Limited; Tulsa (OK); On-site; USD 110,000 - 150,000; Full time

Job summary

Bayer is seeking a Machine Learning Researcher focused on Genomic AI to develop state-of-the-art models for genomic data across crop species. You will build and fine-tune DNA/RNA sequence models, predict variant effects, and link molecular signals to phenotypes, collaborating with biologists, breeders, and computational scientists.

The role involves deploying models in genomic selection and editing workflows, ensuring biological interpretability and rigorous validation across environments.

Qualifications

• PhD in a quantitative life-science field with biology data applications.
• Experience building/training deep learning models on biological sequences or omics data.
• Proficiency with modern DL frameworks and large-scale model training.

Responsibilities

• Design, train, and evaluate deep learning models on genomic data.
• Develop genomic language models to predict variant effects and gene function.
• Create models linking genotype to phenotype across environments.
• Integrate multi-omic data and collaborate with biologists and breeders.
• Operationalize models within genomic pipelines and decision-support tools.

Skills

Deep learning

Biology data analysis

DL frameworks

Scientific communication

Education

PhD in Computational Biology / Bioinformatics

Tools

PyTorch

JAX

TensorFlow

Job description

Bayer is seeking a Machine Learning Researcher focused on Genomic AI to develop state-of-the-art models for genomic data across crop species. You will build and fine-tune DNA/RNA sequence models, predict variant effects, and link molecular signals to phenotypes, collaborating with biologists, breeders, and computational scientists.

The role involves deploying models in genomic selection and editing workflows, ensuring biological interpretability and rigorous validation across environments.