Computational Biologist for AI Drug Discovery [Remote]

Contribute expert computational biology and cheminformatics knowledge to a computational drug discovery project, helping to create, validate, and benchmark realistic tasks and datasets that train and evaluate next-generation AI systems. This remote contractor role centers on analyzing small-molecule data, building reproducible code-based tasks and environments, and providing detailed scientific feedback that improves model performance and real-world relevance. No prior AI experience is required, domain expertise is the priority.

• Analyze and interpret small-molecule and drug discovery datasets using computational biology, bioinformatics, and cheminformatics approaches.
• Curate, annotate, and validate chemical and biological datasets, for example ChEMBL, PubChem, and DrugBank, to support AI-driven discovery workflows.
• Evaluate compound-target interactions, predict and assess ADMET properties, and advise on lead optimization strategies by integrating chemical, biological, and clinical data sources.
• Provide expert guidance on structure-activity and structure-property relationships, medicinal chemistry strategies, and experimental design considerations.
• Build and implement code-based benchmark tasks, including terminal or CLI-based environments, that model realistic computational drug discovery scenarios.
• Develop reproducible environments, for example using Docker, and create automated testing pipelines to ensure task correctness and solvability.
• Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, and deliver detailed written feedback and recommendations.

• Expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or a closely related field; advanced degrees such as PhD, MSc, or PharmD are highly valued but not required.
• Required skills include bioinformatics, biochemistry, ADMET, cheminformatics, molecular docking, and structure-activity relationship analysis.
• Strong coding proficiency in Python beyond analysis scripts, with hands-on experience building tools, pipelines, or testable code.
• Familiarity with version control and collaboration tools, specifically Git and GitHub, and experience using Docker for reproducible environments.
• Experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
• Proven track record in small-molecule drug discovery tasks, including SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
• Comfort working with public chemical and bioactivity databases and integrating diverse datasets for analysis.
• Ability to communicate complex chemical and biological concepts clearly in written feedback and reports.
• Experience in multidisciplinary and remote projects is preferred; familiarity with AI-assisted coding tools is a plus.

• Role type: Contractor.
• Location: Remote.
• Work focuses on contributing domain expertise to a customer computational drug discovery project and on producing high-quality, reproducible tasks and feedback for AI training and evaluation.

• Hourly rate: $80 to $110 per hour.

• No prior experience in AI is required; candidates must have the domain knowledge and technical skills outlined above.