Biology and Bioinformatics Research Specialist – MSc/PhD

Gramian Consulting

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

Posted 11/9/2026contractRemote • United States, Canada, Australia, New Zealand, United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in analyzing and optimizing biological data analysis pipelines, with proficiency in Python and/or R for computational biology applications. Capable of communicating complex scientific concepts effectively to diverse audiences while contributing to the development of AI models and tools in the biological domain.

Highest-signal resume keywords

Python ProgrammingR ProgrammingBiological Data AnalysisStatistical MethodsGenomics Expertise

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

BioinformaticsComputational BiologyNGS Data AnalysisRNA SequencingSingle-Cell DatasetsGenomic VariantsVariant CallingProteomics Data AnalysisStatistical AnalysisAnalytical Reasoning

Soft Skills

Communication SkillsCollaborationCritical Thinking

Tools & Technologies

Biological Data Analysis ToolsAI ModelsComputational Workflows

Industry Keywords

BiologyBioinformaticsComputational BiologyGenomicsProteomics

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design, evaluate, and critique biology, bioinformatics, and computational biology workflows for AI benchmarking initiatives.
Provide expert insights into genomic, transcriptomic, proteomic, and other biological data analysis pipelines.
Assess and optimize computational pipeline parameters, software configurations, and statistical methods.
Analyze biological datasets, including NGS data, RNA sequencing and single-cell datasets, genomic variants and variant calling results, protein structures and proteomics data, and molecular and cellular biology datasets.
Evaluate scientific methodologies and AI-generated biological analyses for accuracy, consistency, and reproducibility.
Identify analytical errors, methodological limitations, and opportunities for improving computational workflows.
Contribute domain expertise to the development and validation of biology-related AI models and tools.
Document findings, methodologies, and best practices to support knowledge transfer.
Communicate complex scientific concepts clearly to technical and non-technical collaborators.

Requirements

What you’ll need

Master's or PhD in Biology, Bioinformatics, Computational Biology, Genomics, or a closely related STEM discipline.
Equivalent professional industry or research experience may also be considered.
Deep expertise in at least one relevant biological or computational specialization.
Hands-on experience analyzing real biological datasets.
PhD holders with industry experience in software engineering, data science, computational biology, or related technology roles are particularly encouraged.
Proficiency in Python and/or R.
Experience with relevant scientific tools, depending on specialization.
Professional written and spoken English proficiency at C1 level or higher.
Strong statistical, quantitative, and analytical reasoning skills.