Computational Biology Specialist (Drug Discovery & AI Training)

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. 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.