Time Commitment: 15+ hours per week Schedule: Flexible micro1 is looking for Computational Life Scientists with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems.
PhD Experts – Health, Applied & Quantitative Sciences
Job description
Position: Life Sciences Research & Benchmarking Expert
Qualification: PhD in a relevant Life Sciences discipline
Engagement: Project-Based / Research Evaluation
About the Role
We are looking for highly qualified PhD professionals in Life Sciences with strong academic research backgrounds, experience working with leading research institutions, and a proven understanding of research benchmarking practices within their respective domains.
The ideal candidates should have experience conducting high-quality research, publishing in reputed scientific journals, and referencing or applying established research benchmarks, methodologies, and standards in their work.
Relevant Research Domains
We are looking for experts with a PhD in one or more of the following disciplines:
- Pharmacology & Toxicology
- Biotechnology
- Bioinformatics & Computational Biology
- Neuroscience
- Immunology
Key Requirements
- PhD in one of the above-mentioned Life Sciences disciplines or a closely related field.
- Strong research experience, preferably affiliated with or gained at Tier-1 universities, research institutions, or reputed laboratories.
- A strong publication record in recognised, high-impact, peer-reviewed scientific journals.
- Hands-on experience with research benchmarking, including the use of established benchmarks, reference standards, frameworks, and evaluation methodologies in their respective domains.
- Ability to identify, interpret, and critically evaluate research benchmarks relevant to their area of expertise.
- Familiarity with leading research standards, methodologies, and benchmarking practices used by the scientific community.
- Strong analytical, literature review, and scientific evaluation skills.
Key Evaluation Areas
Candidates should be able to demonstrate:
- Publication-Based Benchmarking: Identification of benchmarks, reference studies, standards, or evaluation frameworks cited or referenced in their published research.
- Domain Expertise: Knowledge of the leading and most widely recognised benchmarks used in their specific research domain.
- Benchmarking Application: Practical experience applying research benchmarks to evaluate, compare, validate, or improve research outcomes.
- Research Assessment: Ability to assess the credibility, relevance, and effectiveness of different benchmarking approaches within their discipline.
Preferred Candidate Profile
- PhD holders with a strong academic and research track record.
- Researchers with publications in reputed journals and experience collaborating with leading academic or research institutions.
- Professionals who have actively used research benchmarking in their publications, research projects, or professional work.
- Candidates who can clearly explain the top benchmarks and evaluation frameworks relevant to their respective domains.
Screening & Assessment Criteria
As part of the evaluation process, candidates may be assessed on:
- Their published research papers and the benchmarks referenced in those publications.
- The top 3–5 benchmarking frameworks, reference standards, or methodologies they are familiar with in their domain.
- Practical examples of how they have applied these benchmarks in their research.
- Their understanding of how benchmarking is used to compare research findings, validate methodologies, and assess scientific performance.
Note: Strong preference will be given to candidates who have demonstrable experience in research benchmarking, beyond theoretical or academic knowledge alone.
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