Remote Lead Computational Biologist

Summary

Join SandboxAQ's AI Simulation team as we develop new drugs and materials using AI and physics-based computational solutions. We are seeking an experienced Lead Computational Biologist to amplify our ability to reason causally about biological systems, based on multimodal data from a variety of inputs.

Requirements

• PhD in computational biology or similar field with strong innovation and publication record
• 10+ years of relevant professional experience, including pharma/biotech and postdoctoral research
• Experience mentoring direct and/or indirect reports
• Excellent analytical capability, being able to identify key questions and come up with innovative solutions for complex problems
• Unique blend of passion for biology, strong bioinformatics experience (omics, pathway, network analysis, etc.), AI, software development, and literacy on experimental biology to be an effective leader of your team

Responsibilities

• Lead projects combining ML/AI solutions, knowledge graphs, bioinformatics, biophysical simulations, and software development to optimize drug discovery and development strategies
• Guide a technical team to innovate in areas including disease biology, bioinformatics, cheminformatics, AI (e.g., ML, NLP, etc.) using your blend of expertise and knowledge in these areas
• Apply your experience in both technical leadership and people management to build a successful and inclusive team
• Partner with researchers from diverse backgrounds to develop novel computational methods to infer causality in disease progression
• Provide broad insight and lead drug projects by providing support on studies in multiple scientific areas including target identification and validation, biomarker discovery, patient stratification, clinical trial design, etc
• Interpret experimental data from biological studies in immunology, oncology, and neurodegeneration
• Analyze omics and phenotyping data from research studies, clinical trials, and real-world databases to identify disease-driving cell types, pathways, and genes
• Propose drug targets based on the biology insights derived from data and suggest validation experiments

Preferred Qualifications

• Proven background in physics-based and AI-based molecular simulation
• Experience in target identification
• Experience in clinical development or real world data
• Experience with biomarker discovery and translation
• Experience with text mining or competitor information analysis
• Solid biology knowledge in Immunology, Neurodegeneration, and Oncology

Benefits

• Competitive salaries
• Stock options depending on employment type
• Generous learning opportunities
• Medical/dental/vision
• Family planning/fertility
• PTO (summer and winter breaks)
• Financial wellness resources
• 401(k) plans