Full-Time

Computational Chemist

Proxima

Proxima

51-200 employees

AI-driven proximity-based drug discovery platform

No salary listed

Boston, MA, USA + 1 more

More locations: New York, NY, USA

Hybrid

Category
Biology & Biotech (2)
,
Required Skills
Python
Machine Learning
Requirements
  • MSc/PhD degree in Chemistry, Computational Chemistry, Biochemistry, Chemical Engineering, or another related subject
  • Minimum 2 years (PhD) or 4 years (MSc) of post-graduate experience in small-molecule drug discovery
  • Proven track-record in advancing drug discovery projects using in-silico methods; strong background in rational drug design
  • Ability to adapt well to a fast-paced environment and get things done by combining creativity, problem-solving skills, and a can-do attitude to overcome obstacles
  • Extensive experience in large-scale virtual screening using structure and ligand-based methods for hit identification and optimization
  • Strong programming skills with at least 2 years of experience using Python for data analysis
  • Excellent written and verbal communication skills along with a strong desire to work in cross-functional teams
Responsibilities
  • Lead small-molecule drug discovery projects using internal and external Machine Learning and CADD tools
  • Drive drug discovery programs forward by quickly developing scalable tools to address specific project needs
  • Work independently and in collaboration with Medicinal Chemists to prioritize small-molecule designs, clearly communicating the decisions to interdisciplinary audiences
  • Collaborate with experts from other fields (e.g., Medicinal Chemistry, Machine Learning, Computational and Structural Biology, etc.) to advance integrated in-silico discovery platforms
  • Design and execute large-scale virtual screening campaigns using both ligand and structure-based approaches
Desired Qualifications
  • Previous experience in chemically induced proximity (molecular glues, PROTACs, etc.), especially in molecular design or in-silico method development
  • Successful track-record in molecular design, working with Medicinal and Synthetic Chemists
  • Extensive experience with open-source cheminformatics tools such as RDKit, especially in navigating ultra large-scale chemical spaces via similarity searches, clustering, etc.
  • Experience in leveraging experimental data for building and/or refining complex in-silico screening pipelines (e.g. SPR, TSA and cell-based assays readouts, including phenotypic screening)
  • Prior experience in designing chemical screening libraries, including synthesis considerations
  • A solid understanding of deep learning-based frameworks applied in structural design (e.g. RoseTTAFold2, DiffDock, DeepDock, GNINA, KDEEP, dMaSIF)
  • Experience in developing ML tools to predict protein-ligand poses, binding affinity/ranking or generate target-conditioned small-molecules
  • Familiarity with common pitfalls in dataset curation for Machine Learning methods, especially, in the context of small-molecules and proteins
  • Familiarity with best software development practices, prior experience in developing Python packages, package management (pip, mamba, conda), CI/CD and related topics necessary for supporting high-quality codebases
  • Contribution, development, and maintenance of open-source packages used by the small-molecule discovery community

Proxima builds AI-native tools to accelerate drug discovery by studying how proteins interact rather than targeting single proteins. It combines proteome-scale structural data from cross-linking mass spectrometry with an atomistic AI model to design small molecules that can induce, modulate, or block protein interfaces and ternary complexes. The platform enables proximity-based therapies such as molecular glues and PROTACs, addressing targets that were previously hard to drug. Its goal is to become essential infrastructure for the next generation of drug discovery, advancing programs toward clinical trials starting in 2026 through strategic pharma partnerships.

Company Size

51-200

Company Stage

Seed

Total Funding

$80M

Headquarters

New York City, New York

Founded

2019

Simplify Jobs

Simplify's Take

What believers are saying

  • $80M seed round in January 2026 led by DCVC with NVIDIA validates platform scaling.
  • $1.67B Blueprint Medicines deal advances programs to 2026 clinical trials with royalties.
  • SAB additions Deshaies, Jones, Rappsilber bring PROTAC, glue, XL-MS expertise.

What critics are saying

  • Recursion's phenomics AI outperforms Neo-1, eroding partnerships in 12-24 months.
  • Nurix's KT-621 enters Phase 1 trials 6-12 months ahead, capturing autoimmune market.
  • Arvinas PROTAC hold triggers 40% sector valuation drop, hitting Proxima in 3-6 months.

What makes Proxima unique

  • NeoLink generates proteome-scale XLMS data on protein complexes, mapping <5% characterized interactome.
  • Neo-1 unifies de novo molecular generation with multimodal structure prediction for ternary complexes.
  • Proximity therapeutics induce protein interactions via molecular glues and PROTACs for undruggable targets.

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Benefits

401(k) Company Match

401(k) Retirement Plan

Health Insurance

Dental Insurance

Vision Insurance

Unlimited Paid Time Off

Paid Holidays

Paid Sick Leave

Parental Leave

Company Equity

Meal Benefits

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

1%

2 year growth

0%
Business Wire
Mar 5th, 2026
Proxima Appoints Dr. Raymond Deshaies, Dr. Lyn Jones, and Dr. Juri Rappsilber to Scientific Advisory Board

Proxima appoints Dr. Raymond Deshaies, Dr. Lyn Jones, and Dr. Juri Rappsilber to Scientific Advisory Board. New advisors bring decades of industry drug discovery leadership and foundational scientific expertise across Proxima's proximity therapeutics engine and structural proteomics data platform From left to right: Dr. Raymond Deshaies, Dr. Lyn Jones, and Dr. Juri Rappsilber, newly appointed members of Proxima's Scientific Advisory Board. NEW YORK-(BUSINESS WIRE)-Proxima (formerly VantAI), a frontier AI and data generation company discovering the next generation of proximity therapeutics, today announced three appointments to its Scientific Advisory Board: Dr. Raymond Deshaies, co-inventor of the PROTAC concept and widely recognized as one of the founding members of the field of targeted protein degradation; Dr. Lyn Jones, a leader in molecular glue development and chemical biology; and Dr. Juri Rappsilber, who established and continues to pioneer cross-linking mass spectrometry as a foundational tool for structural and systems biology. Proxima's platform is built to develop proximity-based medicines, molecules that unlock new possibilities against disease through co-opting the cell's own biological machinery. "Some of the most powerful drugs ever discovered, such as lenalidomide and thalidomide, turned out to work by hijacking the cell's own protein disposal machinery. Viruses do the same thing: they commandeer ubiquitin ligases to trick the cell into trashing its own antiviral defenses. The principle of induced proximity is using small molecules to leverage tools from nature's playbook, and we've barely scratched the surface of what's therapeutically possible with it," said Dr. Raymond Deshaies, member of the National Academy of Sciences and former SVP of Global Research at Amgen. "What we've lacked is the structural and systems biology data to systematically exploit this principle, and Proxima generates exactly that data at proteome scale." Even where the biology is well characterized, expanding the druggable proteome demands new chemistry that can precisely engage protein interfaces more broadly. "The human genome encodes more than 600 E3 ubiquitin ligases, and thousands of other proteins with potential in proximity applications, but we've built almost everything so far on just two of them," said Dr. Lyn Jones, Principal Investigator at Dana-Farber Cancer Institute and former Chief Scientist of its Center for Protein Degradation. "If we want to expand the druggable proteome, we need to understand the protein interfaces of new effector proteins in detail. To get there, you need structural data on these interfaces at a scale that hasn't yet existed." Pursuing proximity therapeutics rationally, as Deshaies and Jones describe, requires structural data at full cellular interactome scale - a scale that demands rethinking experimental methods themselves. Cross-linking mass spectrometry (XL-MS) has long held promise as a technique that can map native protein interactions, but leveraging it to create data at the scale required by frontier ML methods has not yet been possible. "The limiting factor in cross-linking mass spectrometry has historically been throughput: generating enough distance restraints, across enough of the interactome, to move from validating individual structures to building comprehensive structural models," said Dr. Juri Rappsilber. "Proxima's platform represents an important step in this direction. By industrializing cross-linking mass spectrometry as a critical data modality and pairing it directly with computational structure prediction, Proxima is demonstrating what becomes possible when this data is generated at a depth and scale the field has long envisioned but that has remained elusive until now." Together, these pioneering data modalities form a self-reinforcing flywheel with Proxima's leading frontier ML methods: structural data focused on interfaces deepens understanding of biology and pathways behind disease, helping to direct where small molecule adaptors that modify interactions stand to impact disease in powerful ways. Proxima is already putting this cycle to work alongside leading big pharma partners and advancing new proximity modalities like transcription factor relocalization, epigenetic modifiers, and RIPTACs through programs with innovative partners like Halda Therapeutics (acquired by Johnson & Johnson). About the New Advisors Dr. Raymond Deshaies is a member of the National Academy of Sciences and former Distinguished Fellow and Senior Vice President of Global Research at Amgen. Prior to Amgen, he was a Howard Hughes Medical Institute Investigator (HHMI) at the California Institute of Technology. He co-conceived the PROTAC (proteolysis-targeting chimera) concept with Craig Crews and is widely recognized as one of the founding members and most important voices across the field of targeted protein degradation and proximity therapeutics more broadly. Dr. Lyn Jones is a Principal Investigator and Faculty Member at Dana-Farber Cancer Institute, former Head of Chemical Biology at Pfizer, and Chief Scientist at Dana-Farber's Center for Protein Degradation. His laboratory focuses on next-generation covalent approaches to modulate protein function, with the objective of expanding the druggable proteome. Dr. Juri Rappsilber is Full Professor and Chair of Bioanalytics at Technische Universität Berlin and former Professor of Proteomics at the University of Edinburgh. He has pioneered both the computational and experimental methods that established cross-linking mass spectrometry (XL-MS) as a tool for mapping protein structures and interactions at systems scale, including in native cellular environments. About Proxima Proxima is pioneering a transformative approach to therapeutics by illuminating the dynamic networks of protein interactions that drive biological function. Leveraging a groundbreaking structural proteomics platform and frontier AI models, Proxima generates unprecedented interactomics data, revealing how proteins and small molecules interact and shape cellular behavior at proteome-wide scale. Alongside a robust and mechanistically differentiated internal pipeline, Proxima collaborates extensively with external partners to accelerate the delivery of innovative proximity therapeutics, applying its technology to make previously undruggable targets accessible and provide powerful new ways to target diseases by rewiring cellular circuitry. For more information, please visit www.proximabio.com.

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