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Remote Molecular Modeling Jobs (NOW HIRING)

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... Analyze and interpret small-molecule and drug discovery datasets using advanced computational ...

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Remote Molecular Modeling information

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$11K

$80.7K

$103.5K

How much do remote molecular modeling jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote molecular modeling in the United States is $80,687.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $98,500.00 per year, depending on experience, location, and employer.

What is remote molecular modeling?

Remote molecular modeling refers to the use of specialized software and computational tools to simulate and analyze the structures and behaviors of molecules, all performed from a remote location rather than a physical laboratory. Scientists and researchers can use cloud-based platforms or remote desktop connections to access powerful computing resources, collaborate with colleagues, and conduct experiments virtually. This approach is especially useful for drug design, protein engineering, and material science research, allowing for flexibility and efficient teamwork across different geographic locations.

How does a remote molecular modeling professional typically collaborate with laboratory-based researchers and cross-functional teams?

Remote molecular modeling professionals frequently interact with laboratory scientists, medicinal chemists, and other team members through virtual meetings, collaborative software, and detailed reporting. They often participate in project discussions to interpret simulation results, advise on compound design, and provide computational insights that guide experimental planning. Effective communication and timely sharing of data are essential, as remote modelers bridge the gap between in silico predictions and hands-on laboratory work. This collaborative dynamic ensures that computational findings are seamlessly integrated into broader research efforts.

What are the key skills and qualifications needed to thrive as a remote molecular modeler, and why are they important?

To thrive as a Remote Molecular Modeler, you need a strong background in chemistry, biochemistry, or related fields, typically supported by an advanced degree such as a PhD or MSc. Proficiency with molecular modeling software (e.g., Schrödinger, MOE, AMBER), programming languages (such as Python), and experience with computational chemistry tools are essential. Strong analytical thinking, attention to detail, and effective communication skills help you interpret data and collaborate with cross-functional teams remotely. These competencies are crucial for accurately simulating molecular interactions and contributing to research and drug discovery projects.
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What cities are hiring for Remote Molecular Modeling jobs?

Cities with the most Remote Molecular Modeling job openings:

What are the most commonly searched types of Molecular Modeling jobs?

The most popular types of Molecular Modeling jobs are:

What states have the most Remote Molecular Modeling jobs?

States with the most job openings for Remote Molecular Modeling jobs include:

Infographic showing various Remote Molecular Modeling job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $80,687 per year, or $38.8 per hour.

Cheminformatics Specialist - Remote

micro1 AI

Minneapolis, MN • Remote

$80 - $110/hr

Part-time

Posted 22 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.