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Entry Level Remote Environmental Scientist Jobs in Colorado

Remote Sensing Technician

Denver, CO · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

This is an entry-level position where dedicated individuals with critical thinking and problem ... Ability to work independently as well as in a collaborative team environment; offer constructive ...

Showing results 21-40

Entry Level Remote Environmental Scientist information

What are the most commonly searched types of Remote Environmental Scientist jobs in Colorado? The most popular types of Remote Environmental Scientist jobs in Colorado are:
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What cities in Colorado are hiring for Entry Level Remote Environmental Scientist jobs? Cities in Colorado with the most Entry Level Remote Environmental Scientist job openings:
Infographic showing various Entry Level Remote Environmental Scientist job openings in Colorado as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Fort Collins, CO • Remote

$80 - $110/hr

Part-time

Posted 10 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.