Remote | Computational Biology & Bioinformatics Expert (PhD) — $45–$90/hour
About The Position
This is a remote specialised scientific consulting opportunity for experienced computational biology and bioinformatics professionals. The role applies expertise in genomic data analysis, transcriptomics, proteomics, scientific programming, and reproducible computational workflows to advanced AI training and evaluation initiatives. Professionals will design, review, and assess complex bioinformatics problems, computational workflows, and AI-generated scientific analyses, helping improve the scientific accuracy, reasoning, and reliability of AI systems. Work spans next-generation sequencing and biological data analysis, statistical modelling, pipeline optimisation, scientific benchmarking, and structured technical evaluation. Assignments include developing rigorous research problems, assessing genomic and transcriptomic analyses, evaluating reproducibility and methodology, validating scientific conclusions, and documenting computational methods and findings. The engagement is freelance/contract, fully remote and open worldwide, with compensation of $45–$90 per hour. There are 50 available openings.
Requirements
- PhD in Bioinformatics, Computational Biology, Genomics, or a closely related scientific discipline, or equivalent industry or research experience.
- Advanced expertise in computational biology, bioinformatics, genomics, or related quantitative biological research.
- Hands-on experience analysing real biological datasets, including NGS, RNA-seq, or genomic variant data.
- Strong understanding of molecular biology, genetics, computational research methodologies, and biological data interpretation.
- Practical proficiency in Python and/or R for scientific programming, quantitative analysis, and computational biology.
- Experience with standard bioinformatics tools such as BLAST, samtools, GATK, Bioconductor, Biopython, or equivalent software.
- Experience developing reproducible workflows using Nextflow, Snakemake, or comparable tools.
- Comfort working in Linux and command-line environments for scientific computing and workflow execution.
- Strong understanding of sequencing data processing, quality assessment, alignment, variant calling, and biological annotation.
- Experience analysing genomic, transcriptomic, proteomic, or structural biology datasets.
- Ability to evaluate computational pipeline parameters, software configurations, and statistical methodologies.
- Strong statistical, quantitative, and analytical reasoning capabilities.
- Demonstrated experience developing technically rigorous solutions to complex biological research problems.
- Professional written and spoken English proficiency at C1 level or higher.
- Excellent written and verbal communication skills, including documenting complex scientific methods and clearly explaining technical findings.
- Strong understanding of reproducible research practices, computational validation, and scientific quality assurance.
- Exceptional attention to detail and commitment to accurate, well-documented scientific work.
- Ability to work independently and collaborate effectively with multidisciplinary scientific and technical contributors.
Nice To Haves
- Experience with AI/ML-assisted computational biology workflows, scientific benchmarking, or model evaluation.
- Peer-reviewed publications, patents, or contributions to open-source bioinformatics software.
- Background in single-cell analysis, structural biology, proteomics, or computational drug discovery.
Responsibilities
- Design technically rigorous bioinformatics and computational biology problems based on realistic research scenarios.
- Evaluate genomic, transcriptomic, and proteomic research questions, assumptions, experimental methods, and computational approaches.
- Contribute scientific expertise to AI benchmarking and computational biology evaluation initiatives.
- Analyse biological datasets, including next-generation sequencing, RNA-seq, and genomic variation.
- Evaluate pipelines for sequence alignment, variant calling, biological annotation, and downstream analysis.
- Review transcriptomic and proteomic datasets using established computational and statistical methods.
- Assess data quality, analytical parameters, and computational results, and identify methodological inconsistencies or scientific inaccuracies.
- Develop and evaluate computational biology workflows using Python, R, and relevant scientific software.
- Assess pipeline configurations, computational parameters, and statistical methods for accuracy and reproducibility.
- Apply bioinformatics tools and workflow-management tools to build or review reproducible research workflows.
- Use Linux and command-line environments to evaluate scientific analyses, automated pipelines, and computational processes.
- Design and critique bioinformatics workflows, scientific reasoning tasks, and computational problems for AI benchmarking.
- Review AI-generated biological analyses, programming solutions, and scientific explanations for correctness and completeness.
- Develop accurate reference solutions supported by established biological principles and reproducible methods.
- Provide structured expert feedback to improve AI performance in genomics, computational biology, and bioinformatics.
- Validate workflows, analytical outputs, and scientific conclusions against established research methodologies.
- Evaluate statistical reliability, reproducibility, and technical consistency of bioinformatics analyses.
- Document computational methods, pipeline configurations, and scientific findings clearly.
- Communicate complex biological and computational concepts to scientific and interdisciplinary collaborators.
- Support scientific quality standards, methodological improvements, and knowledge sharing across evaluation activities.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Career Level
Senior
Education Level
Ph.D. or professional degree
