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Computational Biology – AI Specialist
Gramian Consulting. Design complex scientific workflows across computational life sciences requiring multiple analytical and computational steps.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and validating complex scientific workflows in computational life sciences, utilizing strong Python programming skills and experience with scientific datasets and tools. Capable of developing reproducible workflows and ensuring high-quality task execution while incorporating feedback.
Highest-signal resume keywords
PhD In Life SciencesStrong Python Programming SkillsExperience In Scientific ComputingDevelopment Of Reproducible WorkflowsValidation Of Scientific Outputs
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Scientific ComputingData AnalysisComputational MethodsMulti-Step AnalysesScientific Programming
Soft Skills
Independent ValidationAttention To Detail
Tools & Technologies
Scientific LibrariesCommand-Line ToolsDomain-Specific Software
Industry Keywords
Computational Life SciencesScientific WorkflowsAutomated Grading CriteriaTask DependenciesData Packaging
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Design complex scientific workflows across computational life sciences requiring multiple analytical and computational steps.
- Develop realistic scientific datasets, input files, instructions, constraints, and expected deliverables.
- Create tasks requiring AI agents to inspect data, select appropriate methods, execute analyses, and troubleshoot intermediate results.
- Implement reproducible expert solutions and objectively verifiable ground truths.
- Design robust automated or semi-automated grading criteria for scientific tasks.
- Validate scientific assumptions, calculations, code, intermediate outputs, and final results.
- Ensure task dependencies, data, and computational resources can be reliably packaged in controlled environments.
- Develop workflows using Python, command-line tools, scientific libraries, and relevant domain-specific software.
- Ensure tasks assess scientific reasoning and execution rather than memorization.
- Maintain high task quality and throughput while incorporating reviewer feedback.
Requirements
What you’ll need- PhD, postdoctoral experience, or equivalent research experience in Life Sciences or a closely related field.
- Strong Python programming skills with demonstrated experience in scientific computing.
- Experience conducting multi-step computational scientific analyses.
- Experience working with scientific datasets and computational tools.
- Ability to independently validate scientific reasoning, calculations, and computational outputs.
- Experience developing reproducible computational workflows and verifying expected results.
- Familiarity with scientific libraries, command-line tools, or domain-specific life sciences software.
- Experience in scientific research involving computational methods, data analysis, or scientific programming.