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Computational Scientist Rdkit Jobs in Berkeley, CA

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Computational Scientist Rdkit information

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$61.8K

$136.3K

$168.4K

How much do computational scientist rdkit jobs pay per year?

As of Aug 27, 2026, the average yearly pay for computational scientist rdkit in Berkeley, CA is $136,333.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,700.00 and $167,700.00 per year, depending on experience, location, and employer.

What is a computational scientist 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.

How does a computational scientist 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.

What are the key skills and qualifications needed to thrive as a computational scientist 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.

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What cities near Berkeley, CA are hiring for Computational Scientist Rdkit jobs?

Cities near Berkeley, CA with the most Computational Scientist Rdkit job openings:

Computational Scientist Rdkit jobs near you

Applied ML Scientist (Staff / Principal)

Genesis Molecular AI

San Mateo, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. The role involves applying cutting-edge AI to solve real-world drug discovery challenges and serves as a critical bridge between long-term research and experimental drug discovery programs.
Responsibilities:
• Work directly with project teams to assess model performance and utility, including applicability to current project needs, and collaborate with ML and engineering teams to resolve issues or add new functionality.
• Assist experimental colleagues with use and interpretation of model predictions by providing context about model quality and prediction uncertainty.
• Evaluate model quality by validating predictions against project data and internal or external benchmarks.
• Curate internal and external datasets for model training and validation (in collaboration with experimental teams).
• Contribute to design and analysis of experiments on model changes and alternative architectures.
Qualifications:
Required:
• A seasoned computational scientist with a proven track record of machine learning based methods to impact small molecule drug discovery projects.
• A cheminformatics expert, fluent in the language of molecular data with hands-on mastery of tools like RDKit or OpenEye.
• A scientist who speaks the language of experimental drug discovery, with a strong familiarity with common assay types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.).
• A rigorous data scientist, with experience in modeling and analysis of small molecule datasets and passion for statistical validation, uncertainty quantification, and deriving clear insights from complex, noisy data.
• A hands-on applied scientist and software engineer with strong coding skills in Python and a deep practical knowledge of the applied ML toolkit (e.g., scikit-learn, PyTorch).
• An exceptional communicator and collaborator, able to act as the bridge between machine learning researchers and experimental scientists.
• A curious, problem-oriented mind, excited to dive into the emerging field at the intersection of AI, physics, chemistry, and biology and make foundational contributions and discoveries.
• A true team player who thrives in highly collaborative, mission-driven environments where science and engineering are deeply intertwined.
• Inspired by our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite.
Preferred:
• A PhD in Cheminformatics, Computational Chemistry, Computer Science, or a related field.
• A track record of publications applying machine learning to drug discovery challenges.
• Deep expertise in advanced modeling techniques such as graph neural networks, multitask modeling, active learning, or Bayesian optimization.
• Experience with large-scale data management, including SQL databases and data pipelining tools.
• Strong opinions on molecule featurization and model validation.
Company:
Genesis Therapeutics unifies AI and biotech to accelerate the discovery of new medicines. Founded in 2019, the company is headquartered in South San Francisco, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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