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Nomic is building the world's highest-throughput protein profiling platform using proprietary nELISA® technology to enable accessible, scalable proteomics for drug discovery, translational research, and therapeutic development. The company has profiled over 500,000 samples and recently closed a $42M Series B.
As a Profiling Development Associate, you will play a hands-on role at the intersection of biology, engineering, and data. You'll work with cross-functional teams in Automation, Data, Software, and Operations to develop, validate, deploy, and continuously improve high-throughput workflows that power proteomic discovery at scale.
Key responsibilities include:
- Independently execute profiling experiments to validate new workflows and protocol updates, developing detailed experimental plans and generating high-quality, well-documented data
- Support development and troubleshooting by analyzing experimental results, contributing to root cause investigations, and improving workflow performance and data quality
- Contribute to deployment of new workflows through pilot runs, SOP updates, technical documentation, and change control processes
- Support day-to-day lab operations including reagent preparation, instrument readiness, and experimental coordination
You will thrive in a fast-paced, collaborative environment where your work directly impacts the accessibility and reliability of proteomics research.
Requirements:
- M.Sc. in biotechnology or related field, or equivalent qualification
- 1–3 years of hands-on lab experience in academic or industry settings
- Familiarity with techniques such as ELISA, flow cytometry, bead-based assays, bio-conjugation & purification, spectroscopy, microscopy, PCR, or cell culture
- Strong communication skills and ability to document work clearly and completely
- Ability to work independently and collaboratively in a fast-paced environment
- Bonus: Experience with liquid handler automation, conjugation chemistry, or multi-color flow cytometry
- Bonus: Experience handling diverse sample types or working with variable biological matrices
