Computational Biology & Bioinformatics Expert (PhD)

Job Type: Contractor

Location: Remote (Worldwide)

Job Summary: In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities: Design, evaluate, and critique bioinformatics and computational biology workflows to support AI benchmarking initiatives. Provide expert-level insights on genomic, transcriptomic, and proteomic data analysis pipelines. Assess and optimize pipeline parameters, tool configurations, and statistical methods for accuracy and reproducibility. Analyze biological datasets (e.g., NGS, RNA-seq, variant calling, protein structure) and provide actionable recommendations. Leverage domain knowledge to guide the development and validation of biology-related AI models and tools. Communicate complex scientific concepts clearly, both in writing and verbally, to technical and non-technical collaborators. Document findings, methodologies, and best practices to ensure knowledge transfer across the customer’s team. Required Skills and Qualifications PhD in bioinformatics, computational biology, genomics, or a closely related field, or equivalent industry/research experience. Professional written and spoken English (C1 or higher). Hands-on experience analyzing biological data (e.g., NGS, RNA-seq, variant analysis). Proficiency in Python and/or R for scientific analysis, plus experience with standard bioinformatics tools (e.g., BLAST, samtools, GATK, Bioconductor, Biopython). Experience building reproducible workflows with tools such as Nextflow or Snakemake, and comfort working in Linux/command-line environments. Strong statistical, quantitative, and analytical reasoning skills. Outstanding written and verbal communication abilities, with the ability to clearly document and explain technical concepts. Track record of rigorous scientific problem-solving in complex biological domains.

Preferred Qualifications: Experience with AI/ML-assisted biology workflows or benchmarking. Peer-reviewed publications, patents, or contributions to open-source bioinformatics software. Background in single-cell analysis, structural biology, proteomics, or drug discovery. prediction/retrosynthesis.