Senior Research Scientist

Your Role:
Senior Research Scientist
- Target Intelligence and Early Project Lead

As a Senior Scientist in the Mechanistic Biology team, you will lead novel target identification and validation across multiple animal diseases to build the drug discovery pipeline. This is a non-lab role focused on guiding cross-functional teams through early-stage drug discovery by leveraging advanced in vitro techniques, integrated AI/ML-driven platforms, and functional genomics. You will be responsible for accelerating the discovery cycle through high-throughput screening (HTS) approaches to rapidly move from Hit-to-Lead for both small molecules and biologics.

• Target Identification & Discovery Innovation: Lead the identification and prioritization of novel targets using in vitro/in vivo experiments, literature reviews, bioinformatics, functional genomics, and AI/ML. Implement iterative design-test-learn and active learning cycles to optimize lead compounds and accelerate the discovery cycle.
• Screening & Digital Discovery: Design and deploy high-throughput and multi-modal screening strategies—including biochemical, biophysical, and cellular approaches to identify novel chemical and biological starting points. Leverage AI-augmented data analysis, digital phenotyping, and digital discovery platforms to accelerate candidate identification and minimize experimental costs.
• Cross-Functional Discovery Leadership: Guide cross-functional teams through early drug discovery from initial concept through target validation, partnering closely with Computational Sciences, Chemistry, Medicinal Chemistry, Computational Biology, Technical Development, and Preclinical Development. Collaborate with Computational Sciences to develop machine learning models for hit expansion and property prediction.
• Target De-risking, Biomarkers & Translational Models: Develop strategies to de-risk targets and enhance commercial viability by integrating Chemistry, Manufacturing, and Controls (CMC) considerations and assessing on-target/off-target safety risks. Develop and integrate biological, AI-enabled, and imaging biomarker strategies and translational in vitro disease models, including CRISPR/Cas9-edited primary cell lines and organoids, to accelerate discovery.
• External Partnerships & Scientific Advancement: Manage external CRO partnerships and biotech collaborations, providing scientific expertise to support discovery campaigns including DNA-encoded library (DEL), phage display, and yeast display. Foster strategic research collaborations and stay at the forefront of study design, model development, and New Approach Methodologies (NAMs) to maintain a competitive edge in animal health research.

• Education: Ph.D. in Cell/Molecular Biology, Pharmacology, Biochemistry, or a related field with several years of postdoctoral training.
• Experience: Professional experience in industry research and early-stage biotech/drug discovery, including CRO management and experience with integrated digital discovery and HTS platforms.
• Top 2 skills:
  
  Expert in target identification and validation: Including biological assay development for small/large molecules and expertise in high-throughput approaches to validate and identify targets (e.g., DEL, virtual screening).
  Expertise in New Approach Methodologies (NAMs): Such as organoids/iPSCs and CRISPR/Cas9 screening, with high proficiency in using AI/ML and deep learning for target validation and phenotypic profiling.

• 3 years of experience in a pharmaceutical company, preferably in animal health.
• Demonstrated success identifying novel targets and a proven publication record.
• Experience with generative AI (e.g., ProteinMPNN) for de novo protein design and affinity maturation.
• Demonstrated ability to lead projects in a fast-paced, agile environment; ability to collaborate and influence cross-functionally
• Working knowledge of applicable statistical principles and data analysis techniques.
• Experience with compound library screening and biomolecular training (RNA-seq, omics, flow cytometry).