Organoid Modeling AI/ML Scientist

Axle Energy; Bethesda (MD); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Medical, Dental & Vision coverage

PTO & Holidays

401K match

Educational benefits

Referral bonus

FSA & account reimbursements

Job summary

Axle Energy seeks an AI/ML Scientist/Developer to join the NIH-supported Standardized Organoid Model Center on-site in Bethesda, MD. You will develop computational models to predict organoid growth and standardize protocols to advance tissue engineering research.

The role requires a PhD in a relevant field, strong Python/R and ML framework experience, and a track record of applying computational methods to biological data. Strong collaboration with experimental teams is essential.

Qualifications

• PhD in computer science, engineering, applied mathematics, or related field, with demonstrated AI/ML model development experience.
• Strong programming skills in Python or R and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Experience applying computational methods in biological lab settings and knowledge of experimental design and biological data types.

Responsibilities

• Design and implement machine learning models to predict organoid development based on protocols, environment, and molecular data.
• Develop in silico models simulating organoid growth dynamics and identify optimal conditions for reproducibility.
• Create feedback loops between experimental validation and computational prediction to improve protocol standardization.
• Collaborate with experimental teams and data scientists to integrate multi-modal datasets.

Skills

Python

R

AI/ML model development

Machine learning frameworks

Education

PhD in CS/Engineering/Applied Math

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Axle Energy seeks an AI/ML Scientist/Developer to join the NIH-supported Standardized Organoid Model Center on-site in Bethesda, MD. You will develop computational models to predict organoid growth and standardize protocols to advance tissue engineering research.

The role requires a PhD in a relevant field, strong Python/R and ML framework experience, and a track record of applying computational methods to biological data. Strong collaboration with experimental teams is essential.