Accelerating impact through partnerships
Inceptive · Palo Alto, CA · Palo Alto
CHECKED 8H AGO
Bio & Science AIonsitesenior
At a glance
Highlights
- Lead strategic siRNA partnerships at the intersection of AI and RNA therapeutics.
- Serve as primary interface for pharma and academic alliances driving siRNA medicines.
- Coordinate cross-functional discovery teams to deliver partnered RNAi programs.
What they offer
- Quarterly company-wide retreats
- Monthly wellness benefit
- Budget for multiple visits per year to offices in Berlin, Palo Alto or Switzerland
- Learning & Development budget for conferences, courses and professional growth
- Buddy to help you get settled
- Direktversicherung for German Beginners
Ideal candidate
PhD-trained alliance leader passionate about RNA therapeutics and AI-driven discovery who thrives at the science-business interface and building trusted, high-impact partnerships.
Requirements
- Ph.D. or M.S. in Molecular Biology, Biochemistry, Pharmacology or related life sciences field
- 5+ years in alliance management, business development or strategic partnerships in biopharma/biotech
- Working knowledge of oligonucleotide therapeutics, particularly siRNA biology and development
- Experience managing complex multi-party research or licensing collaborations end-to-end
- Exceptional interpersonal, negotiation and communication skills, influencing without authority
- Strong project management skills with proficiency in Linear, Notion or equivalent
- Familiarity with AI/ML in drug discovery, including target ID and ADME/toxicity modeling
- Experience negotiating term sheets, CDAs, MTAs or master research collaboration agreements
- Existing network within the oligonucleotide therapeutics field
Lab profile
About Inceptive
Building foundation models of life to enable AI-designed medicines.
What they build
- Foundation models for biomolecules
- Biological software for medicine design
- AI-designed therapeutics
Known for
- Large-scale generative biomolecule design
- High-throughput experimental data generation
- Tight model-lab feedback loop
- Antedisciplinary collaborative team