Proxima · Boston
OtherBiologyRemoteFullTimeposted 5mo ago
Proxima (formerly VantAI) is a frontier AI and data generation company discovering the next generation of proximity therapeutics 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 with an elite group of VCs including DCVC, NVIDIA’s NVentures, AIX, Yosemite among others.
Neo-1 is our all-atom foundation model that combines state-of-the-art structure prediction and molecular generation in a single system. Neo-1 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 built on proprietary XLMS 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-1, 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 most promising frontiers in modern drug discovery with the potential to treat previously intractable diseases and target ‘undruggable’ proteins. We’re building the tech and the team to make that happen. . Come join us!
We're looking for a Biologist, Cellular Pharmacology to design and execute cell-based assays that validate targets and computationally driven hits across our proximity drug discovery programs. You'll work across the full discovery arc, from target validation through hit ID, hit-to-lead, and lead optimization, owning the cellular pharmacology data that drives internal pipeline decisions and external partner deliverables.
This is a hands-on role: you'll run select assays in-house, manage CROs, and work closely with our structural proteomics data generation platform and computational teams, helping shape how our platform is applied to proximity-based drug discovery.
This is a high-impact role in a small, fast-moving team where your experimental results directly shape the direction of programs.
Design and execute cell-based pharmacology assays to evaluate proximity-inducing compounds (degraders, molecular glues, stabilizers)
Manage CRO relationships for outsourced assays and run high-priority experiments in-house
Characterize compound activity profiles: dose-response, kinetics, selectivity, mechanism of action, and SAR at the cellular level
Build and validate disease-relevant cellular models (engineered cell lines, primary cells, co-culture systems) for target validation and translational pharmacology
Develop and optimize quantitative assay readouts including high-content imaging, flow cytometry, reporter systems, and multiplexed approaches
Collaborate with computational scientists and the XLMS platform team, providing biological feedback to improve ML model predictions and data generation priorities
Prepare data packages for internal decision-making, BD/partnership discussions, and due diligence
PhD in cell biology, pharmacology, molecular biology, or a related discipline
3–8 years of post-PhD experience in a biotech or pharma drug discovery environment, ideally in proximity biology, targeted protein degradation, or molecular glue programs
Deep hands-on expertise in designing and executing cell-based pharmacology assays (degradation assays, ternary complex formation, ubiquitination, reporter systems)
Experience with quantitative cellular techniques: high-content imaging, flow cytometry, AlphaLISA/HTRF, NanoBRET, Western blot, ELISA, and/or proteomics-based approaches (TMT, global proteomics)
Track record of working at the interface of computational predictions and experimental validation
Comfortable working in a fast-paced, resource-constrained environment where you own the experimental design end to end
Strong scientific communication skills; able to present data clearly to computational and medicinal chemistry and biology audiences
Experience with E3 ligase biology (CRBN, VHL, IAPs) or ubiquitin-proteasome pathway
Background in event-driven pharmacology or beyond-Rule-of-5 compound characterization
Experience working and partnering with CROs
Experience supporting IND-enabling studies, including in vivo pharmacology, PK/PD, and biomarker strategies, with working knowledge of preclinical safety requirements