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Cheminformatics Jobs (NOW HIRING)

Xenon7

Research Advisor, Computational Chemistry

This role will bridge molecular simulation, cheminformatics, and machine learning to generate actionable insights that guide the optimization of chemically modified oligonucleotides across our client ...

Satomic

Staff Engineer, Chemical Search

San Diego, CA · On-site

About the role This first cheminformatics hire will design and build the chemistry search engine: the system that exposes our accessible chemical space through query modes fit for how our partners ...

MyGradJob

Postdoctoral

Chapel Hill, NC

$41K - $56K/yr

PhD in Bioinformatics or Cheminformatics Additional Information All your information will be kept confidential according to EEO guidelines.

Jobgether

This is a unique opportunity to work at the intersection of cheminformatics, drug discovery, data engineering, and applied AI. The role focuses on transforming complex and heterogeneous ...

Cadence Design Systems Inc.

$101K - $188K/yr

Apply chemistry/cheminformatics expertise with ML experts to build robust, scalable models to support data-driven decision making. * Work on retrospective and prospective projects both internally and ...

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How much do cheminformatics jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for cheminformatics in the United States is $56.81, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $68.75 per hour, depending on experience, location, and employer.

What job makes $10,000 a month without a degree?

In cheminformatics, high-paying roles typically require advanced education, but some related positions like freelance data consultants or contract specialists can earn around $10,000 monthly through experience and specialized skills. Generally, achieving this income level without a degree is uncommon in technical fields and often depends on expertise, certifications, and industry demand.

How much do cheminformatics data scientists make?

Cheminformatics data scientists typically earn a median salary ranging from $80,000 to $130,000 annually, depending on experience, education, and location. Advanced skills in machine learning, programming, and familiarity with chemical databases can lead to higher compensation, especially in research or pharmaceutical industries.

Do computational chemists make good money?

Computational chemists, including those in cheminformatics, typically earn competitive salaries that vary by experience, education, and industry. Entry-level positions may start around $60,000 annually, while experienced professionals can earn over $120,000, especially in pharmaceutical or biotech sectors. Skills in programming, data analysis, and familiarity with chemical databases can enhance earning potential.

What are the key skills and qualifications needed to thrive in the Cheminformatics position, and why are they important?

To thrive in Cheminformatics, you need a solid background in chemistry, computer science, and data analysis, often supported by a relevant degree in chemistry, bioinformatics, or a related field. Proficiency with cheminformatics software (e.g., RDKit, Open Babel), programming languages like Python or Java, and familiarity with databases such as SQL is highly valued. Strong problem-solving skills, teamwork, and clear scientific communication are essential soft skills for success in this interdisciplinary field. These skills ensure the effective development and application of computational tools to solve complex chemical and pharmaceutical research challenges.

What is a Cheminformatics job?

A Cheminformatics job involves using computational techniques, data analysis, and software tools to manage, analyze, and interpret chemical and molecular data. Professionals in this field apply machine learning, molecular modeling, and database management to support drug discovery, materials science, and other chemistry-related research. They often work in pharmaceutical, biotech, or academic settings, collaborating with chemists and data scientists to accelerate scientific discovery.

What types of projects or tasks can I expect to work on in a Cheminformatics role?

In a Cheminformatics position, you'll typically work on projects involving the analysis and management of chemical data, such as building and evaluating molecular models, developing algorithms for virtual screening, or optimizing compound libraries for drug discovery. Daily tasks often include programming, data visualization, collaborating with medicinal chemists or biologists, and contributing to research publications or presentations. You may also be responsible for maintaining database integrity and ensuring the quality of datasets used in computational experiments. The work is both collaborative and analytical, offering exposure to cutting-edge technology in chemical and pharmaceutical research environments.

How much does a theoretical chemist make?

A theoretical chemist's salary typically ranges from $60,000 to $120,000 annually, depending on experience, education, and location. Advanced roles or those in industry may offer higher compensation, especially with specialized skills in computational modeling and software tools.
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Cheminformatics jobs near you
Infographic showing various Cheminformatics job openings in the United States as of June 2026, with employment types broken down into 40% Full Time, and 60% Contract. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $118,165 per year, or $56.8 per hour.

Research Advisor, Computational Chemistry

Xenon7

Remote

Full-time

Posted 27 days ago

Job description

About us:
Shape the Future with AI, Ignite Your Potential
Xenon7 is an inferno where skill, dedication and passion run together.
About our client:
Global healthcare leader headquartered in Indianapolis, Indiana. The Cardiometabolic Research (CMR) Therapeutic Area of our client, focuses on the discovery of biologic, small molecule and genetic therapeutics for the treatment of cardiometabolic diseases and associated complications.
We are seeking a highly motivated computational chemist to join our team and apply physics-based modeling and cheminformatics to the design of chemically modified oligonucleotide therapeutics.
Oligonucleotide therapeutics-including siRNAs, ASOs, and splice-switching oligonucleotides-occupy a unique chemical space between small molecules and biologics. Each position in a therapeutic oligonucleotide can carry distinct sugar, backbone, and base modifications, creating a vast combinatorial design space that is poorly served by conventional computational chemistry tools. This role will bridge molecular simulation, cheminformatics, and machine learning to generate actionable insights that guide the optimization of chemically modified oligonucleotides across our client's RNA therapeutics portfolio.
Key responsibilities include:
  • Perform molecular dynamics simulations of chemically modified oligonucleotide duplexes and single-stranded species to characterize the structural and thermodynamic consequences of sugar, backbone, and base modifications
  • Apply free energy methods (FEP, thermodynamic integration, MM/PBSA, MM/GBSA) to predict modification-dependent binding affinities, duplex stability, and protein-oligonucleotide interactions
  • Develop and validate force field parameters for novel nucleotide analogs using quantum mechanical calculations, enabling rapid computational evaluation of new chemistries emerging from the medicinal chemistry team
  • Build and apply cheminformatics descriptors and QSAR/QSPR models adapted for chemically modified oligonucleotides, moving beyond sequence-only representations to capture the full chemical diversity of the modification space
  • Collaborate with medicinal chemists and biologists to integrate computational predictions with experimental SAR data, contributing to the identification of optimal modification patterns for on-target potency, selectivity, metabolic stability, and safety
  • Contribute to reusable computational workflows, data assets, and modeling platforms that support cross-program learning and integration with the team's unified machine learning models
  • Present findings to cross-functional teams and contribute to scientific strategy discussions, publications, and patent applications

Requirements
Basic Requirements:
  • PhD in computational chemistry, physical chemistry, chemical physics, biophysics, or a closely related field

Additional Skills/Preferences:
  • Demonstrated expertise in molecular dynamics simulation of nucleic acids or chemically modified biopolymers
  • Experience with free energy calculation methods applied to biomolecular systems
  • Proficiency in cheminformatics toolkits (RDKit, OpenEye, or equivalent) and/or commercial CADD platforms (Schrödinger, MOE)
  • Strong programming skills in Python, with experience in scientific computing libraries
  • Familiarity with machine learning and AI methods applied to molecular sciences, including experience with predictive modeling for molecular properties, chemical optimization, or structure-activity relationships
  • Excellent written and oral communication skills with ability to present complex computational results to diverse scientific audiences including medicinal chemists and biologists
  • Experience with high-performance computing and/or cloud-based simulation environments
  • Demonstrated ability to work collaboratively in cross-functional team environments
  • Experience with force field parameterization for non-standard nucleotide analogs, including QM-derived charge fitting (RESP, AM1-BCC) and torsion parameter development
  • Familiarity with quantum chemical methods (DFT, ab initio) for electronic structure analysis of modified nucleotides and their impact on duplex stability and reactivity
  • Understanding of how chemical modifications influence oligonucleotide secondary structure, folding, and conformational dynamics, including modification-dependent effects on duplex geometry and protein recognition
  • Experience with machine learning approaches for molecular property prediction, including graph neural networks, molecular language models, or transformer-based architectures applied to chemical or biopolymer data
  • Familiarity with molecular representations for modified oligonucleotides (HELM, extended SMILES, or similar macromolecular encoding schemes)
  • Knowledge of oligonucleotide-specific ADME properties, including nuclease-mediated metabolism, plasma protein binding of phosphorothioate backbones, and endosomal escape
  • Track record of peer-reviewed publications demonstrating expertise in computational chemistry applied to nucleic acids or modified biopolymers
  • Deep understanding of nucleic acid structure and chemistry, including familiarity with common therapeutic modifications (2'-OMe, 2'-F, 2'-MOE, LNA/cET, phosphorothioate, GalNAc conjugates)
  • Experience designing computational workflows that integrate with automated experimental platforms and high-throughput screening
  • Proficiency in Rust or other systems-level languages for performance-critical scientific computing is a plus

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