Job Details

Who We Are

Verge is transforming drug discovery by using artificial intelligence and proprietary human data to solve the biggest driver of rising drug costs: high clinical failure rates. To achieve this, we have built one of the field's largest corpuses of multi-modal patient molecular and clinical data, sourced directly from human tissue. Our team of engineers, neuroscientists, and biologists have so far delivered two drugs to clinic, discovered 282 new targets, and signed commercial partnerships worth in excess of $1.6B with Eli Lily and AstraZeneca.

Your Mission

Reporting directly to the Head of Product & Engineering, and working closely with Verge's leadership and technical teams, the Principal/Director, Computational Biology will be responsible for leading the company's Computational Biology work, aiming to deliver high-value insights to biopharma partners and customers that drive their R&D decisions.

Your 12 Month Outcomes

• Deliver two insights reports (e.g. target characterization) to biopharma partners leading to expanded partnerships,
• Develop a novel approach in support of new product development (patient stratification, biomarker discovery, etc.),
• Benchmark and evaluate the company's foundation models for translational tasks, targeting superior performance to current state-of-the-art,
• Work alongside Head of Business Development to grow Verge's proprietary datasets.

You Will...

• Deliver biological insights on therapeutic candidates and disease biology from the analysis of multi-modal data (transcriptomics, genetics, and clinical data)
• Translate high-level business objectives into a scientific workplan
• Synthesize diverse datasets to generate and evaluate hypotheses for target prioritization, mechanism-of-action identification, indication expansion, repositioning, biomarker discovery, and patient enrichment
• Present results to external stakeholders to drive pharma R&D decisions
• Develop and validate benchmarks to evaluate performance of AI models on translational tasks
• Interpret and analyze the output of AI foundation models
• Translate between biological domain knowledge and machine learning objectives

Requirements

Candidates must have:

• PhD in computer science, computational biology, AI/ML, applied statistics, biophysics, or related field, or MS in related field with exceptional professional experience,
• Experience applying computational methods (including probabilistic, statistical, and/or machine learning techniques) to analyze and integrate matched human clinical and molecular data,
• Deep expertise with the multi-omic data integration (transcriptomics, genetics, proteomics, clinical data) and systems biology workflows (gene network, pathway enrichment analysis)
• Track record of delivering novel translational insights that have influenced pharma/biotech R&D decisions(e.g. target discovery, biomarker identification, patient stratification),
• Exceptional data visualization skills,
• Experience leading cross-functional projects with multiple parties including biologists, engineers, AI researchers, and external collaborators
• Excellent coding skills in Python. A demonstrable portfolio (e.g., GitHub, research code, or shared notebooks) is highly preferred.
• Domain knowledge with advanced AI approaches and experience applying them to a biological context
• Excellent communication skills, including explaining complex scientific concepts to cross-functional stakeholders using plots, documents, and presentations

Finally, we seek candidates who embrace our values and way of working:

• Ability to thrive in uncertainty with frequently changing priorities,
• Deep alignment with our values,
• A passion for making an impact on patients.