Description

You will design and implement machine learning algorithms to identify associations between imaging and omics data.

Responsibilities

• Design and implement machine learning algorithms to understand associations between imaging and omics data.
• Collaborate with machine learning scientists, imaging scientists, and computational biologists to integrate solutions into clinical decision-making.
• Analyze complex biological and clinical data to guide drug development and trial design.
• Build and deploy machine learning pipelines for scientific analysis.
• Publish research findings in relevant journals and conferences.

Required Skills

• M.S. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, Bioinformatics, Bioengineering, or a related quantitative field.
• 5+ years of experience developing and applying advanced ML models in research or industry settings.
• Proficiency in Python and scientific programming.
• Extensive experience with PyTorch or TensorFlow.
• Experience with MLOps workflows, including code version control and experiment monitoring.
• Experience with high-performance compute infrastructures.
• Proven ability to transform research ideas into practical applications.

Preferred Skills

• Experience analyzing multimodal data, including Omics (genomics, transcriptomics, multivariate GWAS) and imaging via representation learning.
• Familiarity with multimodal data integration and cross-domain mapping strategies.

Key Skills

Education

M.S. in Computer Science