Staff Research Scientist, Computational Toxicology
About SandboxAQ
SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
About the Role
We are looking for a Staff Computational Biologist / Toxicologist with deep experience in bioinformatics and computational systems biology. As a member of the Large Quantitative Model (LQM) team, you will develop completely new computational tools to reshape drug discovery.
What You’ll Do
- Leverage expertise in computational biology and toxicology to predict ADME/tox properties of new drugs
- Help lead the creation of next-generation technology to do the above
- Work with a cross-functional team of experts to computerize drug discovery
- Apply deep learning approaches to the above. Drive curation of high-quality datasets.
- Write patents, research papers and technical documents. Participate and present at international conferences.
About You
- Ph.D. in computational biology, bioinformatics, computer science, or related data science fields with 4+ years of biopharma industry experience
- Experience with computational methods for ADME/tox and pK/pD prediction, ideally including knowledge graph methods
- Experience with contemporary AI/ML techniques, including deep learning architectures, and ideally including GNNs
- Extensive hands on experience with high-throughput sequencing data, such as RNA-seq, single-cell RNA-seq data, genomic (whole-genome and exome) data, and/or proteomic data, including retrieval of these from public repositories
- Experience leading technical projects
- Advanced proficiency with Python, R, including for ML (i.e. with PyTorch or TensorFlow) and database management
- Excellent communication skills
Nice-to-haves
- Relevant postdoctoral training
- Experience with physics-based simulation e.g. for pK/pD modeling
- Experience in long-context sequence modeling
- Direct experience in drug discovery or development
- Experience with or knowledge of regulatory drug safety evaluations
The US base salary range for this full-time position is expected to be $192k - $269k per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.
SandboxAQ welcomes all.
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