Target Prioritization CS Intern
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. Come join us!
Key Responsibilities:
Support the Target Prioritization Team in building a new prioritization framework suited for the future of proximity modulation, particularly to identify and rank novel therapeutic strategies
Develop methods to integrate qualitative scientific knowledge and market analyses into scorable metrics
Leverage proprietary protein-protein interaction data to link biological pathways to human diseases and uncover druggable vulnerabilities
Create novel computational tools to retrieve, combine, and analyze diverse datasets
Bridge the gap between technical and non-technical team members, applying insights
from cutting-edge research to evaluate drug targets in real-time
Requirements:
Currently enrolled in or a recent graduate from an undergraduate or graduate program in Computer Science
Proven experience in software development, with a strong foundation in Python and full-stack development
Ability to efficiently manage multiple data processing workflows and demonstrate proficiency in data visualization
Quick to learn and apply new concepts in biology and preclinical drug discovery strategies
Strong team player and effective individual contributor
Preferred Qualifications:
Experience with Large Language Models (LLMs) and prompt engineering
Background in biology
History of working on projects that merge qualitative scientific information with quantitative analysis
Previous involvement with financial data to inform strategic decisions
Strong independent work ethic, capable of driving projects and solving complex problems creatively
Additional Information:
This internship offers the opportunity for high-performing interns to transition to full-time positions, reflecting Proxima's commitment to nurturing talent and fostering professional growth within our team. Salary Range: $40-$60 per hour.