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Internship Computational Modeling Scientist Jobs in Alaska

micro1 AI

Bioinformatics Software Engineer

Anchorage, AK · Remote

$80 - $110/hr

Computational Biology & Cheminformatics Expert Role Type: Contractor Location: Remote micro1 is ... Your work will shape how models learn, reason, and perform through high-quality, real-world input.

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Internship Computational Modeling Scientist information

What is the difference between Internship Computational Modeling Scientist vs Data Analyst Intern?

AspectInternship Computational Modeling ScientistData Analyst Intern
Required CredentialsRelevant coursework, programming skills, possibly some experience in modelingStatistics, data analysis, programming, often some coursework or experience
Work EnvironmentResearch labs, tech companies, biotech firms, industry R&DBusiness, finance, healthcare, tech companies
Employer & Industry UsageResearch-focused roles in science and engineering sectorsData-driven decision making in various industries
Search & Comparison IntentUnderstanding modeling roles, technical skills, internship opportunitiesAnalyzing data, skills required, internship details

The Internship Computational Modeling Scientist typically focuses on developing and applying computational models in scientific research or industry R&D, requiring programming and modeling skills. In contrast, a Data Analyst Intern concentrates on analyzing datasets to inform business decisions, often with statistical and data visualization skills. Both roles involve programming and data handling but differ in their focus and industry applications.

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Internship Computational Modeling Scientist jobs near you

Bioinformatics Research Scientist - AI Reviewer

Anchorage, AK • Remote

micro1 AI
Software Development • 11 - 50 employees
Learn more about micro1 AIexternal

$80 - $110/hr

Part-time

Posted 26 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.

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