Senior Research Associate
About Proxima
Proxima (formerly VantAI) is advancing an AI-native approach to drug discovery by making protein interactions programmable. Our platform brings together foundation-model machine learning, a scalable data generation engine, and a partnership track record exceeding $5B in collaborations across the world’s leading biopharma and tech organizations. We’ve recently closed an oversubscribed seed round partnering us with an elite group of sophisticated and dedicated VCs including DCVC, Nvidia’s Nventures, AIX, Yosemite among others.
Neo is our all-atom foundation model that combines state-of-the-art structure prediction and molecular generation in a single system. Neo enables rapid exploration of chemical and structural space for high value, previously intractable targets, and in particular unlocks small molecule proximity therapeutics like molecular glues with AI for the first time.
In parallel, we are developing an advanced structural interactomics platform (NeoLink: https://www.proximabio.com/neo-1#neolink) built on proprietary proteomics technology and a lab equipped with next-generation mass spectrometry instrumentation. This platform produces proteome-scale maps of protein interactions and helps identify small molecules that modulate proximity. Together with Neo, it creates an integrated system capable of co-folding protein complexes while generating candidate small molecules to influence those interactions. Proximity-based therapeutics represent one of the most promising frontiers in modern drug discovery with the potential to treat previously intractable diseases and target ‘undruggable’ proteins. Our technology combines proteome-scale structural data with state-of-the-art generative AI foundation models, and coupled with our talented team of scientists and engineers we are uniquely well-positioned to discover and develop a new class of medicines. Come join us!
About the Role
We are seeking a hands-on Senior Research Associate to join the NeoLink Platform team and drive execution of proteomics experiments that fuel Proxima’s structural interactomics platform. This role will focus on running proteomics sample preparation and LC-MS workflows end-to-end, learning routine maintenance of our next-generation mass spectrometry instrumentation, and contributing to the scale-up of proteome-wide interaction mapping. You will work closely with proteomics scientists, computational biologists, and chemists to generate the proprietary data that trains Neo and powers our drug discovery pipeline.
What You’ll Do
Execute proteomics experiments end-to-end, including sample preparation, and LC-MS data acquisition
Take ownership over early target and hit validation workstreams to drive drug discovery efforts
Operate and maintain LC-MS systems; routine instrument maintenance including column installation, source cleaning, calibration, and system performance QC
Troubleshoot experimental and instrument issues and contribute to continuous improvement of sample preparation workflows
Maintain accurate experimental records in the electronic lab notebook and adhere to strong documentation standards
Collaborate closely with computational biologists, chemists, and other scientists to integrate proteomics data into structural biology and drug discovery workflows
Complete compound management workflows
Must Haves
Bachelor’s/Masters degree in Biochemistry, Chemistry, Biology, or a related scientific discipline
5+ years of hands-on industry experience in a drug discovery, proteomics, or analytical chemistry setting
Demonstrated proficiency in mass spectrometry-based proteomics workflows, with hands-on sample preparation and LC-MS experience required
Strong troubleshooting skills and excellent attention to detail
Ability to manage multiple experiments and timelines independently in a fast-paced environment
Excellent organizational skills with strong record keeping
Nice to Haves
Prior biotech or pharmaceutical industry experience in a platform or drug discovery environment
Experience operating Orbitrap-class instruments (Astral, Exploris, Eclipse, or similar)
Familiarity with proteomics data analysis tools (e.g., Proteome Discoverer, MaxQuant, Skyline, FragPipe)
Experience with click chemistry enrichment and affinity-tag-based peptide capture
Experience with automated sample preparation platforms (e.g., Hamilton, Opentrons)
