M

Medra

Automates lab experiments via AI-powered robotics

Scientist – Biophysical Characterization

Biology & BiotechUpdated on Nov 10
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • A Ph.D. in biochemistry, biophysics, structural biology, or a related discipline with at least 2 years of industry experience, or a B.S./M.S. with at least 6 years of deep, hands-on industry experience.
  • Deep hands-on expertise with surface plasmon resonance (SPR) and/or biolayer interferometry (BLI), including instrument operation, assay development, and data analysis, with a track record of generating high-quality kinetics data.
  • Strong command of binding kinetics theory and practical pitfalls, including avidity, mass transport, regeneration, surface capacity, and fitting model selection.
  • Demonstrated experience developing and qualifying biophysical assays from scratch, including method validation and troubleshooting.
  • Working understanding of antibody structure, function, and the therapeutic antibody discovery and developability process.
  • Strong documentation habits, attention to detail, and the ability to drive multiple workstreams in parallel.

Responsibilities

  • Develop, validate, and run SPR and BLI assays across affinity and kinetics, epitope binning, self-interaction (AC-SINS and BLI-based), and concentration/quantitation formats on platforms including the Carterra LSA and Gator BLI.
  • Design assay strategies for antibody and alternative binder characterization, selecting sensor chemistry, capture approach, regeneration conditions, and analysis models for each target and format.
  • Build new biophysical capabilities end-to-end by scoping needs, evaluating technologies, qualifying instruments, writing standard operating procedures, and preparing validated workflows for autonomous execution.
  • Partner with roboticists and software engineers to translate manual SPR/BLI workflows into reliable, high-throughput autonomous protocols, including sample handling, plate setup, sensor/chip management, and data-pipeline integration.
  • Develop data-analysis and quality-control frameworks for kinetics fitting, binning heatmaps, and developability flags, and interpret results to inform customer go/no-go decisions.
  • Integrate biophysical data with orthogonal characterization, including thermal stability (nanoDSF/DSC), aggregation and monomericity (HPLC-SEC/DLS), and polyspecificity, to provide customers with an integrated developability picture.
  • Work directly with customers to scope characterization campaigns, communicate results, and translate scientific questions into executable assay plans.
  • Maintain experimental records in electronic lab notebooks and drive reproducibility across deployed assays.

Desired Qualifications

  • Hands-on experience with high-throughput SPR platforms such as Carterra LSA and array-based epitope binning.
  • Experience with alternative binder formats, including VHHs, bispecifics, Fc-fusions, or non-Ig scaffolds.
  • Hands-on experience with lab automation and liquid-handling platforms such as Lynx, Tempest, or KingFisher.
  • Experience developing developability assay panels (nanoDSF/DLS, HPLC-SEC/HIC, AC-SINS) and integrating multi-instrument datasets.
  • Experience building analysis pipelines or scripting for high-throughput kinetics data using Python or R.
  • Track record of developing and qualifying new assays or platforms from scratch.

About the Company

Medra

Automates lab experiments via AI-powered robotics

Medra builds a platform that speeds scientific research by automating lab work with AI and robotics. Its Continuous Science Platform has two parts: Physical AI, which uses general-purpose robots to perform lab tasks (like pipetting and handling samples) and connect with standard instruments, and Scientific AI, which analyzes experimental data to find patterns and suggest new experiments, creating a closed loop that learns from results. Scientists can give workflows in natural language, and the system runs experiments at a larger scale and faster pace than manual work. Medra differentiates itself by tightly integrating flexible robotic automation with AI-driven experiment design in a continuous feedback loop, supported by partnerships with biopharma and research organizations. Its goal is to remove data bottlenecks in biology and drug discovery by enabling rapid, high-throughput, automated laboratories.

Company size
51-200
Company stage
Series A
Total funding
$63M
Headquarters
San Francisco, CA
Founded
2021

Recently Posted Jobs

Explore more opportunities at Medra

See more jobs