Senior Principal Scientist, Portfolio In silico Evidence Lead, Computational Biology

The Department of Computational Innovation seeks a scientist to drive in silico evidence generation and advance novel therapeutic candidates through computational bioinformatics approaches, focusing on autoimmune and dermatological disease indications.

Key Responsibilities

• Generate robust in silico evidence packages supporting NTC progression through development milestones
• Lead bioinformatics projects delivering insights on mechanisms of action
• Apply single/spatial omics, machine learning, and AI techniques to build evidence packages
• Collaborate with immunology, dermatology, and experimental biology teams
• Contribute to clinical biomarker discovery and safety/toxicity assessments

Requirements

• Ph.D. in Bioinformatics, Computational Biology, Immunology, or related field
• 7+ years post-doctoral/industry experience in drug discovery and development
• Minimum 3 years drug discovery experience
• Expertise in large-scale biological dataset analysis (RNA-seq, spatial transcriptomics, proteomics)
• Proficiency in machine learning/AI for biological data
• Strong immunology background, particularly dermatology/rheumatology knowledge
• Excellent communication and collaborative skills

Preferred Qualifications

• Clinical biomarker discovery experience
• Data-driven safety/toxicity assessment background
• Familiarity with regulatory requirements in drug development
• Prior dermatology and rheumatology research experience