↳PhD in Data Science, Computer Science, Machine Learning, Cheminformatics, Computational Chemistry, Chemistry, Pharmaceutical Sciences, or a related quantitative discipline completed prior to the fellowship start date. The program is intended for scientists immediately following their PhD training (graduated in 2026).
↳Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent)
↳Demonstrated experience developing and applying deep learning methods to scientific or chemical datasets.
↳Strong programming skills in Python and familiarity with modern machine learning frameworks and architectures, such as graph neural networks, transformers, large language models or foundation models for scientific applications.
↳Experience with data analysis, statistical modeling, and handling large, complex datasets.
↳Strong commitment to learning, innovation, and professional development
↳Ability to work effectively in highly collaborative, multidisciplinary research environments.
↳Excellent communication skills and ability to present complex scientific concepts to diverse audiences.
