AI/ML Scientist for Organoid Modeling & Bioinformatics
Axle
Frederick (MD)
On-site
USD 115,000 - 130,000
Full time
14 days+
Get more replies from employers
Send a job-specific resume in minutes.
Start fresh or import an existing resume
Benefits offered by this job
Paid Time Off and Paid Holidays
401K match up to 5%
Educational Benefits for Career Growth
Employee Referral Bonus
Flexible Spending Accounts
Job summary
A bioscience and IT company is seeking an AI/ML Scientist/Developer to join a team at the National Institutes of Health. This role involves developing computational models to optimize organoid growth using cutting-edge machine learning techniques. Candidates should possess a Master's or PhD in a relevant field, strong programming skills, and prior experience in biological settings. This opportunity offers competitive compensation and a chance to impact research significantly.
Qualifications
Demonstrated experience in AI/ML model development.
Strong programming skills in Python or R.
Experience in biological laboratory settings is necessary.
Responsibilities
Design and implement machine learning models to predict organoid outcomes.
Develop in silico models for replicable organoid generation.
Collaborate with teams to validate models and integrate datasets.
Skills
Python
Machine learning frameworks (TensorFlow, PyTorch)
Applied mathematics
AI/ML model development
Collaboration skills
Education
Master's degree or PhD in computer science, engineering, applied mathematics, or related field
Tools
TensorFlow
PyTorch
scikit-learn
Job description
A bioscience and IT company is seeking an AI/ML Scientist/Developer to join a team at the National Institutes of Health. This role involves developing computational models to optimize organoid growth using cutting-edge machine learning techniques. Candidates should possess a Master's or PhD in a relevant field, strong programming skills, and prior experience in biological settings. This opportunity offers competitive compensation and a chance to impact research significantly.