Computational Biology Specialist (Drug Discovery & AI Training)
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About Us
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
Role Overview
We are looking for an experienced Computational Biology Specialist to support a scientific project focused on improving how advanced AI systems understand biological data and medicinal chemistry problems.
You will analyse complex datasets, review scientific content, develop realistic drug-discovery scenarios, and provide expert feedback on computational biology outputs. The role combines bioinformatics, medicinal chemistry, biological data analysis, and scientific evaluation. Previous AI experience is not required.
CONTRACT: Freelance contractor, paid per completed task
COMMITMENT: Flexible, based on available tasks and project demand
LOCATIONS: Fully remote - GLOBAL
PROCESS: Application review, technical assessment, and onboarding
HOURLY RATE: $90-$120/h
Responsibilities
- Analyse and annotate complex biological and chemical datasets.
- Review scientific content for accuracy, relevance, and clarity.
- Evaluate AI-generated responses related to computational biology and medicinal chemistry.
- Develop realistic problem sets, case studies, and drug-discovery scenarios.
- Apply computational methods to biological and chemical research questions.
- Identify data-quality issues, scientific gaps, and unsupported conclusions.
- Provide structured feedback to improve AI model performance.
- Contribute to data-curation methods and project quality standards.
Requirements
- Advanced degree in Computational Biology, Bioinformatics, Medicinal Chemistry, or a related field.
- Experience applying computational methods to biological or chemical problems.
- Strong knowledge of medicinal chemistry, drug discovery, or molecular design.
- Experience analysing biological datasets and scientific literature.
- Proficiency with relevant bioinformatics, cheminformatics, or data-analysis tools.
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