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Part Time Remote Clinical Data Manager Jobs in Raleigh, NC

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

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Part Time Remote Clinical Data Manager information

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As of Sep 15, 2026, the average hourly pay for part time remote clinical data manager in Raleigh, NC is $55.57, according to ZipRecruiter salary data. Most workers in this role earn between $43.94 and $66.11 per hour, depending on experience, location, and employer.

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Infographic showing various Part Time Remote Clinical Data Manager job openings in Raleigh, NC as of September 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution, with an average salary of $115,589 per year, or $55.6 per hour.

AI Training Specialist - Cheminformatics

Durham, NC โ€ข Remote

micro1 AI
Software Developmentย โ€ขย 11 - 50 employees

$80 - $110/hr

Part-time

Re-posted 13 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 customerโ€™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 โ€” 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, Schrรถdinger, 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.