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Integrate large-scale multiomics data to push the boundaries of predictive modeling in preclinical and clinical research

Requirements

• 6+ years experience in large-scale bulk data analysis (RNA, WES)
• 3+ years applying modern ML architectures to omics data
• Expertise in cancer biology or clinical omics data
• Proficient in Python and shell scripting
• Experience with Git and high-performance computing environments

Responsibilities

• Write scalable Python code to benchmark ML models on preclinical & clinical tasks
• Analyze and report performance of state-of-the-art ML methods
• Suggest improvements and new directions for predictive modeling
• Document code, analysis, and standardize analytical workflows

Other

• PhD in Computer Science, Computational Biology, Bioinformatics, or related field