Analyst Intern Program

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-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. 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.

Our Analyst Intern Program runs for 4 - 6 months (duration is case by case) and typically begins at the beginning of Summer, Fall or Spring semesters. It offers students (BS, MS and PhD) the opportunity to work across different teams and functions, including Computational Biology & Chemistry, AI Science, Software Engineering, Target Prioritization, Business Development & Partnerships and Internal R&D.

The aim of this program is to attract and develop future leaders, scientists and innovators at Proxima by accelerating the development of talent. From day one, analysts will own projects and have opportunities to make a meaningful impact on Proxima’s innovative science and technology. Team placements are made based on business need and analyst skillset. Multiple roles available - high mobility, deep science, real tech, meaningful impact.

Target Prioritization: Utilizing systems biology (e.g. analyzing gene/protein expression data and interactome data from Neo Link) and structural biology (e.g. structural compatibility analysis using Neo-1) approaches to prioritize targets;
Integrate competitive intelligence by assessing investor sentiment, market opportunity and commercial viability against competitor pipelines;
Target evaluation and due diligence of novel targets.

Neo Link
:
Overlay our proprietary Neo Link data with public resources (BioGRID/Int Act/STRING, Dep Map, Open Targets, gnom

AD constraint, GTEx) to find “known vs new-to-science” and high-value gaps, designing an automated way to leverage LLMs to retrieve relevant information in the literature (e.g., protein‑protein interactions experimentally verified by academic labs)

Partnerships and Business Development
:
Identification and evaluation of strategic business partners across Pharma and Biotech landscape;
Work to position the platform or program in a way that aligns with pharma portfolio gaps, therapeutic strategy, and risk tolerance;
Work with BD and Scientific Project Leads to ensure we meet milestones, data packages are partnership‑ready, and partner feedback loops back into program prioritization

Internal pipeline: For a prioritized target, work with the Proxima team to conduct end‑to‑end biological and/or chemistry due diligence and hypothesis generation to propose a new…