Senior Scientist, AI-Driven Multimodal Target Discovery

pharmaessentiausa; Bedford (MA); On-site; USD 120,000 - 190,000; Full time

Job summary

PharmaEssentia invites a Scientist II, Computational Biology, AI & Multimodal Target Discovery to advance target discovery using multi-omics, agentic AI, and predictive modeling. You will build rigorous computational methods linking disease evidence to targets and guide experimental design in collaboration with Immunology, Translational Science and Biologics.

Based at PharmaEssentia's PIRC in the U.S., this role shapes computational capabilities, develops scalable workflows, and ensures

Qualifications

• Ph.D. in Computational Biology, Bioinformatics, Computer Science, or related quantitative field.
• Experience in multi-omics target discovery, AI agent development, or computational structural biology.
• Pharma/biotech drug discovery experience with translational research.
• Proficiency in Python, Java, C#, and R with good software practices.
• Experience with ML/AI methods for biological data and benchmarking.

Responsibilities

• Integrate multi-omics data to identify disease-relevant targets.
• Develop AI agents to support scientific workflows with human review.
• Create target identification frameworks using genetic evidence and knowledge graphs.
• Build perturbation-response models across cell types and conditions.
• Apply structural biology tools for protein structure interpretation.
• Create reusable computational frameworks with versioning and provenance.
• Collaborate with Immunology, Biologics, Translational Science to translate questions.
• Track emerging multimodal methods and adopt beneficial approaches.
• Communicate findings via visualizations, docs, and publications.

Skills

Python

R

Java/C#

multi-omics

single-cell

ML/AI for biology

Git

Documentation

Education

Ph.D. in Computational Biology/Related Field

Tools

Jupyter

Docker

GitHub

Job description

PharmaEssentia invites a Scientist II, Computational Biology, AI & Multimodal Target Discovery to advance target discovery using multi-omics, agentic AI, and predictive modeling. You will build rigorous computational methods linking disease evidence to targets and guide experimental design in collaboration with Immunology, Translational Science and Biologics.

Based at PharmaEssentia's PIRC in the U.S., this role shapes computational capabilities, develops scalable workflows, and ensures