Nurix
Senior Scientist / Principal Scientist, Induced Proximity
Brisbane, California; Brisbane, CA United States
Principal · Drug Discovery Technologies
POSTED 5 NOV
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Senior Scientist / Principal Scientist, Induced Proximity
Help shape Nurix’s induced proximity strategy beyond targeted protein degradation. In this hands-on role, you’ll design and run the assays that validate targets, characterize mechanisms and inform go/no-go decisions, working alongside chemistry, biology and biochemistry partners. It’s a chance to grow your scientific, and potentially leadership, experience in a fast-evolving area of drug discovery with direct exposure to platform-level strategy.
Position Description
The Opportunity
- Nurix Therapeutics, Inc. is seeking a motivated scientist to support and help execute the non-degradative induced proximity research strategy. This individual will contribute hands-on scientific expertise to programs beyond targeted protein degradation, helping advance target validation, mechanism characterization, and candidate optimization efforts. Working closely with the Senior Vice President of Induced Proximity and cross-functional partners in chemistry, biology, and biochemistry, this person will help translate strategic priorities into experimental plans, generate and interpret data that inform go/no-go decisions, and contribute ideas on emerging modalities and technologies worth exploring. This is an opportunity to grow scientific and possibly future leadership experience within a fast-evolving area of drug discovery, with direct exposure to strategic decision-making at the platform level.
- Design, execute, and troubleshoot experiments at the bench; building and running biochemical, biophysical, and cell-based assays to interrogate induced proximity mechanisms and drive program decisions
- Contribute to identification, validation, and prioritization of targets amenable to induced proximity approaches (protein sequestration, gene regulation, stabilizers, and related mechanisms)
- Evaluate and integrate new and emerging induced proximity modalities into the strategic roadmap
- Partner with computational/structural biology to advance rational design and predictive modeling of ternary complex formation
- Present experimental data, interpretations, and recommendations to project teams and executive leadership
- Ensure programs meet key milestones from discovery through candidate nomination and IND-enabling work
- Stay current on the competitive and scientific landscape; publish/present externally to build company visibility as needed
What You’ll Bring
Required Qualifications
- Ph.D. in biology, biochemistry, molecular biology, or a related field
- 5+ years of relevant industry drug discovery experience, including significant direct work on induced proximity modalities (targeted protein degradation, molecular glues, bifunctional degraders, or similar)
- Hands-on biophysical and biochemical assay development to quantify ternary complex formation and cooperativity (e.g. TR-FRET/HTRF, NanoBRET, AlphaLISA, SPR, ITC, MST, and DSF)
- Experience in biochemical assay development of the relevant proximity-induced reaction (e.g. ubiquitination, phosphorylation, acetylation, etc.)
- Cell-based mechanistic pharmacology: Western blot, HiBiT/NanoLuc kinetic readouts, flow cytometry, reporter assays, and dose–response and washout/resynthesis studies to establish on-target mechanism
- Cell line engineering and functional genomics utilizing CRISPR knockout/knock-in, CRISPRa/CRISPRi, and siRNA to validate targets and interrogate effector dependencies
- Target engagement and protein-stability methods: CETSA, NanoBRET target engagement, co-IP/pulldown, and cycloheximide-chase or half-life measurement
- Deep mechanistic understanding of ternary complex biology and cooperativity, the ubiquitin–proteasome and autophagy–lysosomal pathways, non-degradative proximity mechanisms (protein sequestration, stabilization, induced phosphorylation/dephosphorylation, transcriptional regulation), and structure-based drug design
- Rigorous experimental design and quantitative data analysis, including assay qualification and QC (e.g., Z′, dynamic range), curve fitting in GraphPad Prism or equivalent, screening-data handling (Genedata Screener or similar), and disciplined ELN documentation