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.