We are sharing a specialised remote consulting opportunity for experienced Computational Biology and Bioinformatics Experts with advanced expertise in genomic data analysis, transcriptomics, proteomics, scientific programming, and reproducible computational workflows to contribute their scientific knowledge to advanced AI training and evaluation initiatives.
Selected professionals will design, review, and evaluate complex bioinformatics problems, computational biology workflows, and AI-generated scientific analyses. The work combines advanced biological research expertise with next-generation sequencing, statistical modelling, pipeline optimisation, and structured technical evaluation to improve the scientific accuracy, reasoning, and reliability of advanced AI systems.
Key Responsibilities
Computational Biology & Scientific Problem Development
- Design technically rigorous bioinformatics and computational biology problems reflecting realistic scientific research scenarios
- Apply advanced biological knowledge to evaluate genomic, transcriptomic, and proteomic research questions
- Develop scientifically accurate challenges involving biological datasets, computational methods, and analytical interpretation
- Assess research assumptions, experimental methodologies, and computational approaches for technical consistency
- Contribute specialised scientific expertise to AI benchmarking and computational biology evaluation initiatives
Genomics, Transcriptomics & Biological Data Analysis
- Analyse complex biological datasets involving next-generation sequencing, RNA-seq, and genomic variation
- Evaluate bioinformatics pipelines for sequence alignment, variant calling, biological annotation, and downstream analysis
- Review transcriptomic and proteomic datasets using established computational and statistical methodologies
- Assess biological data quality, analytical parameters, and interpretation of computational results
- Identify methodological inconsistencies, scientific inaccuracies, and opportunities to improve biological data analysis
Bioinformatics Pipelines & Reproducible Workflows
- 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 such as BLAST, samtools, GATK, Bioconductor, Biopython, or comparable applications
- Build and review reproducible research workflows using Nextflow, Snakemake, or equivalent workflow management tools
- Work within Linux and command-line environments to evaluate scientific analyses, automated pipelines, and computational processes
AI Training & Scientific Benchmark Evaluation
- 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
- Identify errors involving biological assumptions, statistical interpretation, computational methodology, and analytical reasoning
- Develop accurate reference solutions supported by established biological principles and reproducible scientific methods
- Provide structured expert feedback to improve AI performance across genomics, computational biology, and bioinformatics applications
Scientific Validation & Research Documentation
- Validate computational workflows, analytical outputs, and scientific conclusions against established research methodologies
- Evaluate the statistical reliability, reproducibility, and technical consistency of bioinformatics analyses
- Produce clear documentation explaining computational methods, pipeline configurations, and scientific findings
- Communicate complex biological and computational concepts effectively to scientific and interdisciplinary collaborators
- Support consistent scientific quality standards, methodological improvements, and knowledge sharing across evaluation activities
Ideal Profile
- 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 closely related quantitative biological research
- Hands-on experience analysing real biological datasets, including NGS, RNA-seq, or genomic variant analysis
- 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 the ability to document complex scientific methods and explain technical findings clearly
- Experience with AI/ML-assisted computational biology workflows, scientific benchmarking, or model evaluation is advantageous
- Peer-reviewed publications, patents, or contributions to open-source bioinformatics software are highly valued
- Background in single-cell analysis, structural biology, proteomics, or computational drug discovery is beneficial
- 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
Engagement Details
- Freelance / contract engagement
- Fully remote — open worldwide
- Compensation: $45–$90/hour
- 50 available openings
- Specialised scientific consulting role spanning computational biology, bioinformatics, genomics, scientific programming, and AI evaluation
- Qualification Requirement: Relevant PhD or equivalent industry or research experience
- Language Requirement: Professional English proficiency at C1 level or higher
- Technical Requirements: Python and/or R, relevant bioinformatics tools, reproducible workflow development, and Linux/command-line proficiency
- Work will involve scientific problem development, genomic and transcriptomic analysis, computational workflow assessment, and AI-generated solution evaluation
- Relevant focus areas include NGS analysis, RNA-seq, variant calling, proteomics, structural biology, and quantitative biological research
- Assignments will require scientific reasoning, accurate computational methods, technical documentation, and reproducible results
- Professionals will contribute to benchmarking and scientific quality assessment through structured technical feedback and methodological review
- Collaboration may involve computational biologists, bioinformatics researchers, scientific programmers, and multidisciplinary technical contributors
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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