Remote | STEM Expert – Biology & Bioinformatics (PhD) — $45–$90/hour

24-Mag•New York, NY

7d•Remote

About The Position

This is a remote freelance/contract scientific consulting role for experienced Biology, Bioinformatics, and Computational Biology experts. The consultant contributes advanced domain expertise to AI training and benchmarking initiatives by designing, reviewing, and evaluating complex biological research problems, computational workflows, and scientific reasoning tasks. Work spans biological data analysis, genomics and transcriptomics, proteomics, statistical modelling, bioinformatics software, and reproducible computational research. Assignments may include developing technically rigorous research problems; analysing biological datasets; assessing sequencing and other computational workflows; reviewing scientific software, statistical approaches, and reproducibility; evaluating AI-generated analyses and explanations; and producing reference solutions, technical feedback, and research documentation. The opportunity is fully remote and open worldwide, with compensation of $45–$90 per hour. The role is offered through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities.

Requirements

A 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.
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.
Practical proficiency in Python and/or R for scientific programming, biological data analysis, and computational research.
Strong statistical, quantitative, and analytical reasoning capabilities.
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.
A demonstrated track record of rigorous scientific problem-solving in complex biological or computational research domains.
Strong attention to detail and commitment to accurate, reproducible, and well-documented scientific work.

Nice To Haves

Experience in biological network analysis, drug discovery, computational pharmacology, or biostatistics.
Familiarity with bioinformatics tools such as BLAST, samtools, GATK, Bioconductor, Biopython, or comparable specialised software.
Experience developing reproducible computational workflows using Nextflow, Snakemake, or comparable workflow management tools.
Familiarity with Linux, command-line environments, and automated bioinformatics pipelines.
Experience with AI/ML-assisted biological research, scientific benchmarking, or AI model evaluation.
Peer-reviewed publications, patents, or contributions to open-source bioinformatics software.

Responsibilities

Develop technically rigorous biology and computational biology problems based on realistic research scenarios.
Analyse scientific questions involving molecular biology, genetics, cellular processes, and biological systems.
Evaluate research assumptions, experimental methods, analytical approaches, and biological interpretations.
Design scientific reasoning tasks involving biological datasets, computational methodologies, and quantitative interpretation.
Contribute expert insights to biology-focused AI benchmarking assignments.
Analyse genomic, transcriptomic, proteomic, and other biological datasets using appropriate methods.
Evaluate NGS, RNA-seq, single-cell analysis, and variant-calling workflows.
Review data-processing pipelines, including sequence alignment, quality control, biological annotation, and downstream statistical analysis.
Assess protein structures, molecular datasets, and computational biology applications.
Identify methodological inconsistencies, analytical errors, and improvements to biological data interpretation.
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.
Review statistical techniques, data transformations, and computational procedures used in biological research.
Support reproducible analyses using scripting, workflow management, and scientific computing practices.
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 in biological assumptions, data interpretation, statistical reasoning, and computational procedures.
Develop technically accurate reference solutions based on established biological principles and reproducible methods.
Provide structured expert feedback to improve AI performance across biological and computational research domains.
Evaluate research methodologies, computational outputs, statistical conclusions, workflow reproducibility, software configurations, analytical assumptions, and data quality.
Produce clear technical documentation describing research methods, computational procedures, and scientific findings.
Communicate biological and computational concepts to scientific and interdisciplinary collaborators.
Support scientific quality standards, knowledge sharing, and methodological improvement.
Complete work without using confidential or proprietary information belonging to an employer, client, institution, or other third party.