FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.

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 • India, Australia, Japan, New Zealand, United States, Canada, United KingdomMid-LevelSeniorWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in analyzing and optimizing biological data analysis pipelines, with a strong focus on genomic, transcriptomic, and proteomic datasets. Proficient in Python and/or R, with the ability to communicate complex scientific concepts effectively to diverse audiences.
Highest-signal resume keywords
Master's Or PhD In BiologyBioinformaticsComputational BiologyProficiency In Python And/or RStatistical And Analytical Reasoning Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Biological Data AnalysisNGS Data AnalysisRNA SequencingSingle-Cell DatasetsGenomic VariantsVariant CallingProtein StructuresProteomics DataComputational Pipeline OptimizationAI Benchmarking
Soft Skills
Communication SkillsKnowledge Transfer
Tools & Technologies
Scientific Tools
Industry Keywords
GenomicsComputational WorkflowsBiology-Related AI ModelsMethodological LimitationsAnalytical Errors
Tech Stack
Tools & technologiesPython
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.