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Computational Scientist Rdkit Jobs (NOW HIRING)

This gives our computational scientists something rare: a direct, high-throughput bridge from in ... RDKit, OpenEye); real experience inside the drug-discovery loop (SAR, MPO, DMTL cycles, lead ...

... 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 ...

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 ...

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 ...

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 ...

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 ...

Flavors Science & Technology Computational Sciences Lead Responsibilities * Design and implement ... Experience with cheminformatics tools (e.g., RDKit, OpenEye) and molecular analysis techniques such ...

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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 Aug 12, 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 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 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 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.
More about Computational Scientist Rdkit jobs
What cities are hiring for Computational Scientist Rdkit jobs? Cities with the most Computational Scientist Rdkit job openings:
What states have the most Computational Scientist Rdkit jobs? States with the most job openings for Computational Scientist Rdkit jobs include:
Infographic showing various Computational Scientist Rdkit job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 87% Full Time, 7% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.

Machine Learning Scientist/Senior Machine Learning Scientist - Agents for Applied Small Molecul[...]

SwiftCruit

San Francisco, CA • On-site

$147.60 - $274/hr

Other

Posted 7 days ago


Job description

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

Join the small-molecule team within AI for Drug Discovery (AI4DD), formerly Prescient Design, at Roche and Genentech’s Computational Sciences Center of Excellence as a Machine Learning Scientist / Senior Machine Learning Scientist building agents for applied small-molecule drug design. You will develop autonomous, LLM-driven agentic workflows that orchestrate ML models, physics-based methods, and cheminformatics tools to accelerate discovery, working with world-class chemists and structural biologists.

The Opportunity:
  • Design, build, and apply agentic workflows and ML models for key challenges in small-molecule drug design.

  • Fine-tune foundation models for drug discovery relevant topics using internal and external datasets and tools.

  • Optimize agent-derived hypotheses in close collaboration with world-class computational and medicinal chemists and structural biologists.

  • Drive scientific impact through publications, open-source releases, and conference talks.

  • Collaborate widely with computational and experimental researchers at Roche and with academic partners.

Who you are:
  • You are experienced developing LLM-driven agents for scientific workflows and you understand how to orchestrate tools and models reliably.

  • You bring strong machine-learning foundations in linear algebra, probability and optimization, with hands‑on experience with GNNs, sequence/language models and reinforcement learning.

  • You are fluent in Python and modern agentic coding environments such as LangChain, ML frameworks such as PyTorch or JAX, as well as cheminformatics toolkits like RDKit or OpenEye.

  • You hold a PhD or equivalent research depth in machine learning, computer science, chemical engineering or a related quantitative field such as physics or statistics, with up to 2 years of industry research experience (Scientist) or 2+ years of industry research experience (Senior Scientist).

  • You have a record of scientific excellence evidenced by journal and conference publications or a public portfolio of relevant projects (e.g. hosted on GitHub/GitLab).

Preferred:
  • Hands‑on experience orchestrating multi‑tool or multi‑agent scientific pipelines.

  • Hand‑on experience working along the small molecule drug discovery value chain and an excitement to engage with chemists.

  • Familiarity with structural biology datasets.

Relocation benefits are NOT available for this opportunity

The expected salary range for this position, based on the primary location of San Francisco, is $147,600 - $274,000 for the ML Scientist, and $167,400 - 310,800 for the Senior ML Scientist. For the primary of location of New York City, $141,100 - $262,100 for the ML Scientist, and $160,100 - 297,300 for the Senior ML Scientist. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Benefits

#ComputationCoE

#tech4lifeComputationalScience

#tech4lifeAI

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

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