Job Description:

• Design, evaluate, and critique biology, bioinformatics, and computational biology workflows for AI benchmarking initiatives.
• Review genomic, transcriptomic, proteomic, and other biological data analysis pipelines for scientific accuracy and reproducibility.
• Assess and optimize pipeline parameters, software configurations, and statistical methods.
• Analyze biological datasets, including next-generation sequencing (NGS), RNA-seq, single-cell data, variant-calling outputs, and protein structures.
• Validate computational approaches and provide actionable recommendations to improve scientific reliability.
• Apply domain expertise to guide the development and evaluation of biology-focused AI models and tools.
• Document methodologies, findings, limitations, and best practices to support reproducible research and knowledge transfer.
• Communicate complex scientific concepts clearly to both technical and non-technical stakeholders.

Requirements:

• PhD in Biology, Bioinformatics, Computational Biology, Genomics, or a closely related STEM field, or equivalent industry or research experience.
• Professional written and spoken English proficiency at C1 level or higher.
• Deep expertise in at least one relevant biological or computational research area.
• Hands-on experience analyzing real biological datasets.
• Proficiency in Python and/or R for scientific analysis.
• Experience with relevant tools and libraries, such as BLAST, samtools, GATK, Bioconductor, or Biopython, depending on the candidate's specialization.
• Strong statistical, quantitative, analytical, and scientific reasoning skills.
• Excellent written and verbal communication skills, including the ability to explain technical methods and document results.
• Demonstrated ability to solve complex biological or computational problems rigorously.

Benefits: