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Computational Scientist Rdkit Jobs (NOW HIRING)

1910

Computational Theoretical Chemist II

Boston, MA · On-site

We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers ... Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

1910

Computational Theoretical Chemist I

Boston, MA · On-site

We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers ... Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

Givaudan

Cheminformatics Scientist

Cincinnati, OH

$80K/yr

Enhance databases and computational pipelines to support data-driven research. * Develop ... Experience with cheminformatics tools (e.g., RDKit, OpenEye) and molecular analysis techniques such ...

1910

Computational Theoretical Chemist II

Boston, MA · On-site

... science, and software engineering to develop drugs for previously undruggable targets. Role ... Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

1910

Computational Theoretical Chemist III

Boston, MA · On-site

... science, and software engineering to develop drugs for previously undruggable targets. Role ... Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

1910

Computational Theoretical Chemist III

Boston, MA · On-site

We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers ... Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

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All JobsComputational Scientist Rdkit Jobs

Computational Scientist Rdkit information

See salary details

$50.5K

$111.3K

$137.5K

How much do computational scientist rdkit jobs pay per year?

As of Jun 30, 2026, the average yearly pay for computational scientist rdkit in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What is a Computational Scientist specializing in RDKit?

A Computational Scientist specializing in RDKit is a professional who uses computational methods and the RDKit cheminformatics toolkit to analyze and model chemical structures and reactions. They often work in fields like drug discovery, materials science, or chemical engineering, leveraging RDKit for tasks such as molecular fingerprinting, property prediction, virtual screening, and data visualization. Their expertise combines advanced programming skills, a strong understanding of chemistry, and the ability to develop or optimize algorithms for chemical data analysis.

What are the key skills and qualifications needed to thrive as a Computational Scientist working with RDKit, and why are they important?

To thrive as a Computational Scientist using RDKit, you need a strong background in cheminformatics, computational chemistry, and programming, typically with an advanced degree in chemistry, bioinformatics, or a related field. Proficiency in Python, familiarity with RDKit libraries, and experience using molecular modeling and data analysis tools are essential. Critical thinking, problem-solving, and effective collaboration are important soft skills for translating scientific questions into computational solutions. These competencies enable accurate molecular data analysis, innovation in research, and successful teamwork in interdisciplinary environments.

What is the difference between Computational Scientist Rdkit vs Computational Chemist?

AspectComputational Scientist RdkitComputational Chemist
Required CredentialsDegree in Chemistry, Bioinformatics, or related; programming skills in Python; familiarity with RDKitDegree in Chemistry, Chemical Engineering, or related; strong background in molecular modeling and programming
Work EnvironmentResearch labs, biotech companies, pharmaceutical firms; focus on software development and data analysisAcademic or industrial labs; focus on experimental design, molecular simulations, and data interpretation
Industry UsageUsed in cheminformatics, drug discovery, and molecular data analysisApplied in pharmaceuticals, materials science, and chemical research

Computational Scientist Rdkit specializes in developing and applying cheminformatics tools using RDKit, often combining programming and data analysis. Computational Chemist focuses on molecular modeling, simulations, and chemical research. While both roles require chemistry knowledge and programming skills, the Computational Scientist Rdkit role emphasizes software development and data processing, whereas the Computational Chemist emphasizes experimental and theoretical chemistry applications.

How does a Computational Scientist working with RDKit typically collaborate with chemists and software engineers on research projects?

Computational Scientists specializing in RDKit often work closely with chemists to translate scientific questions into computational workflows, such as molecule property prediction or virtual screening. They also collaborate with software engineers to integrate RDKit functionalities into larger platforms or to optimize code for performance and scalability. Effective communication and project management are essential, as these interdisciplinary teams rely on regular meetings, shared documentation, and iterative feedback to ensure research goals are met efficiently. This collaborative environment not only fosters scientific innovation but also provides opportunities to learn from experts in related fields.
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Computational Scientist Rdkit jobs near you

Computational Theoretical Chemist II

1910

Boston, MA • On-site

Full-time

PTO

Posted 5 days ago

Key responsibilities

  • Own computational chemistry programs across therapeutic modalities, disease targets, and indications.

  • Provide key computational chemistry insights to collaborate with Biology, Medicinal Chemistry, ML Engineering, and AI Research teams during drug discovery operations.

  • Co-author provisional patents and peer-reviewed research papers.

Job description

Company Overview
We are the only AI-native biotech, pioneering small and large molecule therapeutics discovery by integrating massive multimodal data, frontier AI models, and high-throughput lab automation into an infrastructure for AI-enabled drug discovery.
We hire top 1% talent to join our interdisciplinary team of scientists, engineers, researchers, operators, innovators, drug developers, business professionals, and technologists.
Join us to build the world's first AI infrastructure for tech-enabled drug discovery and to deliver a pipeline of diverse drug modalities for all major disease areas.
Computation is revolutionizing drug discovery. Advances in big chemical data, massive computing power, artificial intelligence, and molecular dynamics simulation are changing the way we develop new drugs. At 1910 , we put computation at the heart of drug discovery, blending expertise in computational chemistry, structural biology, pharmacology, data science, and software engineering to develop drugs for previously undruggable targets.
Role Description
  • Own computational chemistry programs across therapeutic modalities, disease targets, and indications
  • Ensure effective collaboration with the Biology and Medicinal Chemistry teams by providing key computational chemistry insights to aid in the Hit-to-Lead and Lead Optimization phases of drug discovery operations
  • Ensure effective collaboration with the ML Engineering and AI Research team by providing key computational chemistry insights to aid in the development of AI/ML models for drug discovery as well as the incorporation of those models into drug discovery operations
  • Teach key computational chemistry principles to your cross-disciplinary colleagues from Medicinal Chemistry, AI Research, Machine Learning Engineering, Cell Biology, and Pharmacology
  • Partner to improve 1910's existing process for progressing from computational hit to experimental hit to lead to drug candidate
  • Co-author provisional patents and peer-reviewed research papers
  • Progress a virtual hit to a biochemical/cellular hit
  • Validate a cellular hit in a clinically relevant animal model of disease
  • Update provisional patents with the animal model data
  • Nominate a lead candidate for progression into IND-enabling studies
  • Attend and present research at conferences and events related to computational modeling in drug discovery

Qualifications
  • Ph.D. in computational chemistry or related discipline
  • 2 years of relevant industry experience within drug discovery or biotechnology
  • Played a key role in advancing a drug discovery program from early research phases to clinical development
  • In-depth knowledge and hands-on experience with quantum chemical (QC) methods, including semi-empirical and density functional theory (DFT) approaches, molecular dynamics (MD) simulations, including both standard MD and enhanced sampling techniques such as metadynamics, umbrella sampling, and replica exchange MD, free energy simulations such as FEP and TI, and QM/MM methodologies for small and large molecular systems
  • Strong understanding of key concepts, including potential energy surfaces (PES), intermolecular and intramolecular forces/interactions, force fields, molecular properties, thermodynamic properties, solvation models (implicit/explicit), and conformational sampling
  • Proficiency in analyzing molecular properties such as solvation free energy, dipole moments, vibrational frequencies, electrostatic potential, charge distribution, and more.
  • Deep knowledge of implicit and explicit solvent models, with extensive experience modeling solvent effects on molecular systems and chemical reactions in various environments
  • Extensive experience in using and troubleshooting software tools for QC calculations (e.g., ORCA, xTB, CREST, etc.), MD simulations (e.g., GROMACS, OpenMM, etc.), Drug Design Development Packages (e.g., EG, Schrodinger, MOE, CRESSET)
  • Experience working with HPC Clusters and cloud-based services like (e.g., Microsoft AZURE, AWS)
  • Ability to optimize computational simulation protocols for efficient resource usage
  • Proven experience working with small organic molecules and large biomolecular systems (e.g., peptides, proteins, etc.) for property prediction, conformational analysis, and structure-activity relationships (SAR)
  • Hands-on experience with Python and Bash scripting for automating workflows and data analysis
  • Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data management
  • Basic knowledge of machine learning (ML) techniques applied to molecular property prediction, virtual screening, and related tasks
  • Strong desire to collaborate with AI scientists, data scientists, medicinal chemists, and biologists to interpret computational results and guide experimental design
  • Clear and effective communication of complex scientific ideas through reports, presentations, and publications

Nice to Haves
  • Publications in computational chemistry related to drug discovery

#LI-Onsite
Diversity and Inclusion (1910's Promise)
At 1910, we believe that a diverse, equitable, and inclusive workplace furthers relevance, resilience, and longevity. We encourage people from all backgrounds, ages, abilities, and experiences to apply. 1910 is proud to be an equal-opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. If, due to a disability, you need an accommodation during any part of the interview process, please let your recruiter know. While 1910 supports visa sponsorship, sponsorship opportunities may be limited to certain roles and skills.
Benefits and Perks
  • Competitive compensation package
  • Above market benefits
  • Generous vacation and parental leave
  • Super cool team building activities
  • Great colleagues

Apply