Computational Biologist — AI-Driven Drug Discovery

Tempus AI; Boston (MA); On-site; USD 90,000 - 150,000; Full time

Job summary

Tempus AI seeks a Scientist II to join our Computational Biology, Pharma R&D team. The role focuses on integrating large-scale molecular and clinical datasets to generate actionable insights for drug discovery and translational science, and building next-generation tools that enhance impact and efficiency.

The successful candidate will combine strong computational and statistical skills with biology expertise, engaging with external stakeholders and leveraging AI (foundation models, LLMs) to

Qualifications

• PhD or equivalent with computational biology focus.
• Proficiency in R and/or Python for bioinformatics and data analysis.
• Experience with large-scale biological datasets and translational science.

Responsibilities

• Pharma collaboration & strategy: partner with collaborators to address questions in target discovery and biomarker development.
• Computational analysis: integrate genomic, transcriptomic, imaging, and clinical data; apply stats and ML methods.
• AI & LLM innovation: use LLMs and agentic workflows to accelerate research tasks.
• Method development: implement new methods for real-world and omics data analysis.
• Cross-functional collaboration: work with Research, Clinical, Data Science, and Engineering teams.
• Scientific communication: present results to technical and non-technical stakeholders.

Skills

Machine Learning

Statistical analysis

Cancer biology knowledge

Big data analysis

Communication skills

LLM-based coding assistants usage

Education

PhD in Computational Biology/ Bioinformatics/ Biostatistics/ ML or related field

Master’s degree with 3+ years of relevant experience

Tools

R

Python

SQL

Job description

Tempus AI seeks a Scientist II to join our Computational Biology, Pharma R&D team. The role focuses on integrating large-scale molecular and clinical datasets to generate actionable insights for drug discovery and translational science, and building next-generation tools that enhance impact and efficiency.

The successful candidate will combine strong computational and statistical skills with biology expertise, engaging with external stakeholders and leveraging AI (foundation models, LLMs) to