Computational Biology & Bioinformatics Expert (PhD) - Remote

Location: Worldwide
Work Arrangement: Fully Remote
Employment Type: Independent Contractor
Compensation: $86,400–$172,800/year equivalent
Hourly Rate: $45–$90/hour

Annualized compensation is an illustrative equivalent based on 40 hours/week × 48 weeks/year. Actual earnings depend on hours worked, project availability, and approved work.

About the Role

We are seeking a highly skilled Computational Biology & Bioinformatics Expert with a PhD or equivalent advanced research experience to contribute to the development and evaluation of next-generation AI systems.

In this remote contractor role, you will apply your expertise in computational biology, bioinformatics, genomics, and scientific programming to help train and benchmark AI models. You will evaluate complex biological data workflows, assess analytical methods, and provide expert guidance that improves how AI systems interpret, reason about, and solve scientific problems.

The ideal candidate combines strong computational and statistical capabilities with practical experience analyzing biological datasets and building reproducible research pipelines.

Key Responsibilities

• Design, evaluate, and critique bioinformatics and computational biology workflows for AI training and benchmarking initiatives.

• Provide expert-level guidance on genomic, transcriptomic, and proteomic data analysis pipelines.

• Analyze biological datasets, including next-generation sequencing (NGS), RNA-seq, variant-calling results, and protein structure data.

• Assess and optimize pipeline parameters, tool configurations, and statistical methods to improve accuracy, reliability, and reproducibility.

• Evaluate computational methods and recommend improvements to complex biological analysis workflows.

• Apply domain expertise to support the development, testing, and validation of biology-focused AI models and tools.

• Communicate complex scientific concepts clearly to both technical and non-technical collaborators.

• Document analytical findings, methodologies, workflow configurations, and best practices to support knowledge transfer.

Required Qualifications

• PhD in Bioinformatics, Computational Biology, Genomics, or a closely related discipline, or equivalent professional research or industry experience.

• Professional written and spoken English proficiency at C1 level or higher.

• Hands-on experience analyzing biological datasets, including NGS, RNA-seq, and genomic variant analysis.

• Proficiency in Python and/or R for scientific computing and biological data analysis.

• Practical experience with standard bioinformatics tools and libraries such as BLAST, samtools, GATK, Bioconductor, and Biopython.

• Experience developing reproducible computational workflows using tools such as Nextflow or Snakemake.

• Comfort working in Linux environments and using command-line tools.

• Strong statistical, quantitative, and analytical reasoning skills.

• Excellent scientific problem-solving abilities and attention to methodological rigor.

• Strong written and verbal communication skills, including the ability to explain and document complex technical concepts.

Preferred Qualifications

• Experience with AI/ML-assisted biology workflows, scientific model evaluation, or AI benchmarking.

• Peer-reviewed scientific publications, patents, or contributions to open-source bioinformatics software.

• Experience in specialized areas such as single-cell analysis, structural biology, proteomics, or computational drug discovery.

• Familiarity with molecular and computational methods used in drug discovery, including prediction and retrosynthesis workflows.

Core Technical Skills

• Programming and scientific computing: Python, R, scientific programming, quantitative analysis.

• Bioinformatics: BLAST, samtools, GATK, Bioconductor, Biopython.

• Workflow development: Nextflow, Snakemake, Linux, command-line environments.

• Biological data analysis: NGS, RNA-seq, genomics, variant analysis, transcriptomics, proteomics, and protein structure analysis.

• AI and computational research: AI/ML-assisted biology workflows, model benchmarking, workflow evaluation, and reproducibility.

Candidates with strong computational biology and bioinformatics expertise, rigorous research backgrounds, and an interest in advancing AI-driven scientific discovery are encouraged to apply.