Computational design of biological experiments for model development

At Inceptive, you will help pioneer the next generation of AI-designed drugs, with the potential to positively impact billions of people, as part of a collaborative, antedisciplinary team. We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches. Those models learn from diverse biological datasets and are refined through focused experimentation, large-scale training, and feedback from lab measurements. Progress depends not only on building better models, but also on understanding what they learn, where they fail, how data shapes their behavior, and how to evaluate them against biologically meaningful objectives. You will collaborate closely with AI researchers and biologists to rigorously characterize the behavior, capabilities, and limitations of biological foundation models and their applications. You will identify valuable datasets, develop meaningful evaluations, investigate model behavior, and generate insights that guide model development, data strategy, and experimental priorities across the company. Your Mission, should you choose to accept it Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise Investigate how model performance changes with data quantity, data quality, dataset composition, and training methodology Develop biologically meaningful evaluations and benchmarks that measure progress toward therapeutic design objectives Design and execute rigorous experiments to understand the behavior, capabilities, and limitations of biological foundation models Identify sources of potential artifacts, bias, and noise in biological datasets Identify promising biological datasets for model training and evaluation, and develop computational pipelines for preprocessing, quality control, and exploratory analysis. Design studies, in silico or in the lab, that reveal what models have learned and which biolog