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Life Sciences Research & Benchmarking Experts – PhD

Truelancer AI Truelancer AI ContractRemote — USA $50–60/hr
Posted Nov 6, 2026 · ✓ Still open — checked 15 hours ago

Quick facts

Pay
$50–$60/hr
Type
Contract
Location
Remote — USA
Background
PhD
Platform
Truelancer AI — 101 open jobs
Typical pay at Truelancer AI
$12–80/hour · median $58 (54 jobs on our site)
Payout
Not published by Truelancer AI
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Position: Life Sciences Research & Benchmarking Expert
Qualification: PhD in a relevant Life Sciences discipline
Engagement: Project-Based / Research Evaluation

About the Project

We are seeking highly qualified PhD professionals in Life Sciences with strong academic research backgrounds, experience working with reputed research institutions, and a demonstrated understanding of research benchmarking practices within their respective domains.

The selected professionals will contribute their subject-matter expertise to evaluate, identify, and analyse key research benchmarks, methodologies, standards, and reference frameworks used across different life sciences disciplines.

Relevant Research Domains

Candidates must hold a PhD in one or more of the following disciplines:

Health, Applied & Quantitative Sciences

  • Pharmacology and Toxicology

  • Biotechnology

  • Bioinformatics and Computational Biology

  • Neuroscience

  • Immunology

Key Responsibilities

  • Apply domain-specific research expertise to identify and evaluate established research benchmarks.

  • Review scientific publications and identify the benchmarking frameworks, reference studies, datasets, standards, and methodologies cited or referenced.

  • Identify leading and widely recognised benchmarks used within their respective research domains.

  • Assess how benchmarking practices are applied in academic research, experimental studies, and industry-related research.

  • Analyse and compare research methodologies, evaluation criteria, and performance standards.

  • Provide insights into emerging benchmarking trends and their relevance within the respective scientific fields.

  • Support research evaluation through evidence-based analysis and expert insights.

Required Qualifications & Experience

  • PhD in one of the relevant Life Sciences disciplines mentioned above.

  • Strong research experience, preferably gained through reputed Tier-1 universities, research institutions, or recognised laboratories.

  • A strong publication record in reputed, peer-reviewed scientific journals.

  • Demonstrated experience in conducting, reviewing, or evaluating scientific research.

  • Prior experience using research benchmarking methodologies, reference datasets, established standards, or comparative research frameworks within their domain.

  • Strong understanding of leading research benchmarks and their applications in the relevant discipline.

  • Excellent analytical, critical-thinking, and scientific communication skills.

Key Screening & Evaluation Criteria

Candidates will be evaluated based on the following:

  1. Academic & Research Credentials: PhD qualification, institution reputation, research specialisation, and publication record.

  2. Publication-Based Benchmarking: Ability to identify and explain the benchmarks, reference studies, datasets, or standards cited in their published research.

  3. Domain Benchmarking Knowledge: Awareness of the most widely recognised and influential benchmarking frameworks used in their respective fields.

  4. Practical Application: Demonstrated experience in applying research benchmarks to evaluate, compare, or validate research findings.

  5. Subject-Matter Expertise: Depth of knowledge and familiarity with current research developments in their specialisation.

Preferred Candidate Profile

  • Researchers with publications in high-impact journals.

  • Professionals affiliated with leading universities, research centres, or recognised scientific institutions.

  • Candidates who have actively used established benchmarking standards or reference frameworks in their research.

  • Researchers who can clearly explain the rationale behind selecting particular benchmarks and their relevance to the domain.

Guidelines

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