We are sharing a specialised remote consulting opportunity for experienced Biology, Bioinformatics, and Computational Biology Experts with advanced expertise in biological data analysis, scientific programming, genomics, molecular biology, and quantitative research to contribute their knowledge to AI training and benchmarking initiatives.

Selected professionals will design, review, and evaluate complex biological research problems, computational workflows, and scientific reasoning tasks. The work combines advanced domain expertise with genomic and transcriptomic analysis, proteomics, statistical modelling, bioinformatics software, and reproducible computational research to improve the scientific accuracy and analytical capabilities of advanced AI systems.

Key Responsibilities

Biological Research & Scientific Problem Development

• Develop technically rigorous biology and computational biology problems reflecting realistic research scenarios
• Analyse complex scientific questions involving molecular biology, genetics, cellular processes, and biological systems
• Apply specialised biological knowledge to evaluate research assumptions, experimental methods, and analytical approaches
• Design scientific reasoning tasks involving biological datasets, computational methodologies, and quantitative interpretation
• Contribute expert-level insights to the development and evaluation of biology-focused AI benchmarking assignments

Genomics, Transcriptomics & Biological Data Analysis

• Analyse genomic, transcriptomic, proteomic, and other biological datasets using appropriate scientific methods
• Evaluate next-generation sequencing (NGS), RNA-seq, single-cell analysis, and variant-calling workflows
• Review data processing pipelines involving sequence alignment, quality control, biological annotation, and downstream statistical analysis
• Assess protein structures, molecular datasets, and relevant computational biology applications
• Identify methodological inconsistencies, analytical errors, and opportunities to improve biological data interpretation

Bioinformatics Pipelines & Scientific Programming

• Develop and evaluate computational workflows using Python, R, and relevant bioinformatics software
• Assess scientific software configurations, pipeline parameters, and computational methods for accuracy and reproducibility
• Apply appropriate tools such as BLAST, samtools, GATK, Bioconductor, Biopython, or equivalent applications
• Review statistical techniques, data transformations, and computational procedures used in biological research
• Support the development of reproducible analyses using appropriate scripting, workflow management, and scientific computing practices

AI Training & Computational Biology Evaluation

• Design and critique biology-related questions, bioinformatics workflows, and scientific reasoning chains for AI benchmarking
• Review AI-generated biological analyses, computational solutions, and scientific explanations for correctness and completeness
• Identify errors involving biological assumptions, data interpretation, statistical reasoning, and computational procedures
• Develop technically accurate reference solutions supported by established biological principles and reproducible methodologies
• Provide structured expert feedback to improve AI performance across genomics, molecular biology, bioinformatics, and computational research

Scientific Validation & Research Documentation

• Evaluate biological research methodologies, computational outputs, and statistical conclusions for scientific consistency
• Assess workflow reproducibility, software configurations, analytical assumptions, and data quality
• Produce clear technical documentation describing research methods, computational procedures, and scientific findings
• Communicate sophisticated biological and computational concepts effectively to scientific and interdisciplinary collaborators
• Support consistent scientific quality standards, knowledge sharing, and methodological improvement across specialised research assignments

Ideal Profile

• PhD in Biology, Bioinformatics, Computational Biology, Genomics, or a closely related STEM discipline, or equivalent industry or research experience
• Deep expertise in at least one relevant biological or computational research specialisation
• Demonstrated hands-on experience analysing real biological datasets and developing scientifically rigorous interpretations
• Strong understanding of biological research methodologies, molecular processes, and quantitative scientific analysis
• Expertise in genomics, next-generation sequencing, transcriptomics, single-cell analysis, or related molecular data applications
• Alternatively, advanced experience in proteomics, structural biology, molecular and cell biology, or systems biology
• Experience in biological network analysis, drug discovery, computational pharmacology, or biostatistics is also relevant
• Practical proficiency in Python and/or R for scientific programming, biological data analysis, and computational research
• Familiarity with bioinformatics tools such as BLAST, samtools, GATK, Bioconductor, Biopython, or comparable specialised software
• Strong statistical, quantitative, and analytical reasoning capabilities
• Experience evaluating scientific software configurations, pipeline parameters, and computational results
• Ability to assess complex biological datasets, identify methodological inconsistencies, and recommend technically justified improvements
• Professional written and spoken English proficiency at C1 level or higher
• Excellent written and verbal communication skills, including the ability to explain advanced scientific concepts clearly
• Demonstrated track record of rigorous scientific problem-solving in complex biological or computational research domains
• Experience developing reproducible computational workflows using Nextflow, Snakemake, or comparable workflow management tools is preferred
• Familiarity with Linux, command-line environments, and automated bioinformatics pipelines is advantageous
• Experience with AI/ML-assisted biological research, scientific benchmarking, or AI model evaluation is beneficial
• Peer-reviewed publications, patents, or contributions to open-source bioinformatics software are advantageous
• Strong attention to detail and commitment to accurate, reproducible, and well-documented scientific work

Engagement Details

• Freelance / contract engagement
• Fully remote — open worldwide
• Compensation: $45–$90/hour
• 50 available openings
• Specialised scientific consulting role spanning biology, bioinformatics, computational biology, 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
• Work will involve biological problem development, bioinformatics workflow assessment, scientific data analysis, and AI-generated solution evaluation
• Relevant specialisations include genomics, transcriptomics, proteomics, molecular biology, systems biology, biostatistics, and computational pharmacology
• Assignments will draw on practical experience analysing biological data and evaluating computational research methodologies
• Collaboration may involve scientific researchers, computational specialists, and multidisciplinary project contributors
• Responsibilities will include technical feedback, scientific documentation, and methodological quality assessment
• Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

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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