Head of Computational Chemistry

tl;dr

General Proximity is a seed-stage startup developing the next generation of induced proximity medicines (IPMs). Our OmniTAC drug discovery engine furnishes molecules that co-opt existing cellular machinery to overcome therapeutic challenges which have remained unapproachable to other modalities for decades.

We are seeking a first-rate computational chemist to help us pioneer this uncharted frontier of drug discovery.

Our Story

A long-standing challenge in drug discovery is the development of molecules capable of modulating difficult or undruggable targets. Disease-causing proteins can be dysfunctional in many different ways but our armamentarium for fixing them is quite limited. The most common mechanism of action for FDA-approved drugs is inhibition1 but there are many other possible perturbation types whose potential remains unrealized.

General Proximity is a seed-stage drug discovery company developing a novel platform technology to solve this problem. We make bifunctional drugs that induce the modification of drug targets by existing cellular machinery (rather than through direct modulation by the drug the classical approach).

Historically the development of technologies that allow one to push new buttons in biology has been an incredibly fertile field for the discovery of new medicines2 3 4 and our technology holds the same promise.

The Position

We areseekingan experienced Head of Computational Chemistry to build and lead our computational chemistry cheminformatics and molecular design capabilities. This role will drive small-molecule drug discovery programs by providing strategic and practicalmodelingsupport implementing modern computational workflows and building the cheminformatics and AI-enabled infrastructure needed to empower medicinal chemists and project teams.

The successful candidate will be both a scientific leader and a hands-on drug designer: someone who can partner closely with medicinal chemists structural biologistsbiologistsand DMPK scientists to guide compound design from hit identification through lead optimization and candidateselection. They will alsodeploy practical tools that improve decision-making accelerate design-make-test-analyzecycles and make computational and AI-driven methods accessible to bench chemists.

The ideal candidate is a computational drug hunter who combines deep technicalexpertisewith practical medicinal chemistry judgment. This person should not be an isolated modeler but a true project partner who sits with chemistry teams understands the design problem proposes molecules helps interpret data and builds tools that make the broader organization faster and smarter.

This role is ideal for someone who has worked in a pharma or biotech computational chemistry group and wants to build a modern AI-enabled computational platform from the ground up whileremainingdirectly involved in molecule design.

WhatYoullDo

Computational Chemistry and Molecular Design

• Provide hands-on computational chemistry support to small-molecule discovery programs from target evaluation hit identification hit-to-lead and lead optimization through candidate nomination.
• Apply structure-based and ligand-based design approaches to guide compound design including docking molecular dynamics pharmacophoremodeling QSAR scaffold hopping virtual screening FEP/free-energy methods and multi-parameter optimization.
• Use structural biology data including X-ray structures cryo-EM structures homology models and AlphaFold-derived models to generate actionable design hypotheses.
• Partner withthemedicinal chemistry team to interpret SARoptimizepotency selectivity physicochemical properties ADME/PK developability and synthetic feasibility.
• Lead computational design discussions with project teams and translate complexmodelingresults into clear practical medicinal chemistry recommendations.
• Support portfolio prioritization by evaluating target tractabilityligandability binding-site quality chemical matter and developability risks.

Cheminformatics and Data Infrastructure

• Build and maintain a scalable chem and bioinformatics infrastructure to support compound registration structure-searching SAR analysis property visualization compound triage library design and project decision-making.
• Implement tools for chemical data handling including similarity and substructure searching R-group analysis matched molecular pairs reaction enumeration compound clustering property prediction and visualization.
• Work with internal or external engineering and data science teams to integrate chemical biological DMPK structural and assay data into usable project dashboards and design tools.
• Establish best practices for chemical data quality assay-data curation compound annotation metadata standards and reproducible computational workflows.
• Evaluate implement andmaintaincommercial and open-source computational tools including platforms such as Schrodinger MOE CCDC toolsChemAxon KNIME Pipeline PilotRDKitDataWarrior Spotfire and related systems.

AI/ML and Digital Chemistry Tools

• Lead the practical implementation ofuser-friendlyAI/ML-enabled molecular design tools including generative chemistry predictive ADME/Tox models property prediction active learning virtual screening and decision-support systems.
• Identifyopportunities to incorporate AI tools into the DMTA cycle including compound prioritization library design synthetic route ideation molecular-property prediction and design hypothesis generation.
• Promote AI literacy across chemistry and project teams by training scientists onappropriate use limitations and interpretation of predictive models.
• Build workflows that allow medicinal chemists to usemodeling and AI tools without requiring deep computationalexpertise.

Leadership and Strategy

• Define the computational chemistry strategy for the company and align it with discovery portfolio needs.
• Serve as the internal subject-matter expert for computational chemistry cheminformatics AI-enabled design and molecularmodeling.
• Establish external collaborations with CROs software vendors academic groups AI drug discovery companies and computational chemistry consultants whereappropriate.
• Represent computational chemistry in portfolio reviews program strategy discussions investor diligence scientific advisory board meetings and external collaborations.
• Maintain awareness of emerging computational AI and cheminformatics technologies and recommend adoption where scientifically and operationally justified.

About You

High Agency. Initiative independence and self-accountability are some of our most valued traits.

Enthusiastic. We love people who are excited about what they are doing and are generally attempting to build a high-energy team.

Intensity and Grit. Early-stage startups are hard. Drug discovery is doubly so. We are looking for candidates who have a demonstrated ability to stick with complex problems for the long haul with a team that has your back along the way.

Prosocial. We are here to create life-saving medicines for the patients who need it most. You should be too.

Qualifications & Nice-To-Haves

• PhD in Computational Chemistry Medicinal Chemistry Chemical Physics Biophysics Cheminformatics Physical Organic Chemistry or a related discipline
• A minimum of 15 years of relevant experience in pharma biotech or a drug discovery-focused research environment
• Demonstrated track record of using computational chemistry to impact small-molecule drug discovery programs ideally through lead optimization candidate selection IND-enabling studies or clinical development
• Deep expertise in structure-based drug design ligand-based design docking molecular dynamics virtual screening QSAR FEP/free-energy methods pharmacophore modeling and multi-parameter optimization
• Strong working knowledge of medicinal chemistry principles SAR interpretation physicochemical property optimization ADME/PK concepts and developability considerations
• Practical experience with cheminformatics platforms chemical databases chemical data curation compound registration systems and project-facing visualization tools
• Experience with AI/ML applications in molecular design including predictive modeling generative chemistry active learning or AI-enabled compound prioritization
• Strong programming or scripting ability preferably Python with experience using cheminformatics toolkits such as RDKit and modern data science workflows
• Ability to communicate complex computational concepts clearly to medicinal chemists biologists executives and non-specialist stakeholders
• Demonstrated ability to lead cross-functional teams mentor scientists and influence project strategy without relying solely on formal authority
  
  
• Nice to have:
  • Experience building computational chemistry or cheminformatics capabilities in a biotech or fast-moving discovery organization
  • Experience implementing user-friendly modeling tools for medicinal chemists
  • Familiarity with cloud-based or high-performance computing environments
  • Experience with automated DMTA workflows electronic lab notebooks compound management systems assay-data systems and integrated discovery platforms
  • Experience supporting discovery across multiple modalities such as covalent inhibitors molecular glues degraders etc.
  • Familiarity with synthetic accessibility prediction retrosynthesis tools reaction enumeration and library design
  • Strong external scientific reputation through publications presentations patents open-source contributions or demonstrated project impact

Benefits

• Strong equity incentives. We are looking for candidates who will bring a strong sense of ownership to drive their project areas forward and we believe that you deserve to be compensated accordingly.
• Top tier medical dental and vision coverage One Medical membership.
• 401(k) retirement plans.
• Education and health/fitness incentive programs.
• Meditation retreatsdo a ten-day Vipassana retreat without counting towards vacation days.
• Reading budget! We will buy you books.
• Located in the MBC BioLabs at 135 Mississippi Street an entrepreneurial hub full of the best scientists and operators the Bay Area has to offer. Our lab is a very short walk from the 22nd St Caltrain Station and a number of wonderful restaurants and cafés.

About Us

Work Hard/Play Hard. We believe time is our most valuable commodity so we strive to create a culture that reflects this. We wont drag you through unnecessary meetings or email you at 7 PM on a Saturday. When were at work were there to get things done and when were off were really off.

Strong Communication. We like well-written documents over PowerPoints OKRs over vague mission statements and weekly one-on-ones over yearly reviews.

Writing First. We have a writing-first culture. We believe that clarity of writing reflects clarity of thinking and that the benefits of well-written documentation in a scientific environment are innumerable: democratization of ideation and decision-making increased reproducibility quicker scaling and onboarding and better company-wide alignment to name a few.

Growth. As an early-stage startup we value scientists with an independent can-do attitude. The more hats you can wear the better. Our job as employers is to put you in positive feedback loops so you can grow in the direction of your choosing.

Title and compensation commensurate with experience. Applications from candidates of diverse backgrounds women and members of underrepresented minority groups are particularly welcomed. We look forward to hearing from you. :)

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