More jobs:
Researcher; Ecological, Evolutionary & Environmental Sciences/Health, Applied & Quantitative Scienc
Job in
Chicago, Cook County, Illinois, 60601, USA
Listed on 2026-11-06
Listing for:
AppLab Systems, Inc
Full Time
position Listed on 2026-11-06
Job specializations:
-
Research/Development
Research Scientist, Data Scientist, Biology, Ecology -
Science
Research Scientist, Data Scientist, Biology, Ecology
Job Description & How to Apply Below
Title: Researcher (Ecological, Evolutionary & Environmental Sciences/ Health, Applied & Quantitative Sciences)
Location: Remote
Type: Contract (1099 Independent)
Rate: $100-$120 / hr on 1099
We need PhDs in life sciences (long-list below) with research experience (based on publications in major journals) and working experience of using research datasets in their domains.
- Ecological, Evolutionary & Environmental Sciences ( Ecology / Evolutionary Biology / Marine Biology / Environmental Science )
- Health, Applied & Quantitative Sciences ( Pharmacology / Toxicology / Biotechnology )
- Review scientific content, publications, and research data within your area of expertise.
- Navigate and utilize leading research datasets, repositories, and databases relevant to your discipline.
- Curate, validate, and organize scientific data.
- Identify incorrect, inconsistent, incomplete, or potentially misleading information.
- Verify scientific claims against published research and established datasets.
- Assess data quality, relevance, and reliability.
- Support data annotation, classification, and quality assurance activities.
- Apply critical scientific thinking to evaluate research outputs and data sources.
- Clearly communicate findings and recommendations.
- PhD completed or recently completed in a relevant Life Sciences field.
- Up to 5 years of professional, academic, or postdoctoral experience.
- Demonstrated research experience through publications, thesis work, laboratory research, or postdoctoral projects.
- Experience working with scientific datasets and research databases.
- Familiarity with commonly used datasets, repositories, and data sources within your area of specialization.
- Strong analytical and problem-solving skills.
- Exceptional attention to detail.
- Ability to identify errors, inconsistencies, and quality issues in scientific data.
- Strong written and verbal communication skills.
- Experience with data curation or data quality review.
- Experience using public scientific repositories and databases.
- Bioinformatics, computational biology, or data analysis experience.
- Familiarity with AI-driven research tools.
- Experience reviewing scientific literature and validating scientific content.
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