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Job Summary
We seek a Research Scientist with expertise at the interface of machine learning, data science, and the chemical sciences to lead the AI for the Chemical Sciences Summer Bootcamp. This individual will design and deliver an intensive, hands-on educational program while working closely with CCE faculty and external experts. The Research Scientist will also support post-bootcamp research integration, enabling participants to apply AI/ML methods to active research projects across CCE. The role is central to building sustainable computational infrastructure, curriculum, and collaborative research pathways in AI-enabled chemistry.
Essential Job Duties
Lead the design, development, and delivery of a two-week immersive summer bootcamp on AI/ML for the chemical sciences.
Develop and teach lectures and hands-on computational laboratories covering data curation, molecular representations, machine learning models, deep learning, generative models, and applications in reactions, catalysis, and spectroscopy.
Coordinate with CCE faculty and invited guest lecturers to integrate domain expertise into the curriculum.
Provide year-round mentorship and technical support to bootcamp participants as they transition AI/ML skills into active research projects within CCE laboratories.
Develop and maintain computational workflows, datasets, and teaching materials for reuse and long-term integration into CCE training programs.
Support interdisciplinary research collaborations that combine experimental and computational approaches.
Contribute to the development or operation of shared automation or robotic experimentation platforms linked to AI-driven research.
Publish and disseminate methodological or applied research outcomes arising from bootcamp-enabled projects.
Assist with assessment, reporting, and continuous improvement of the bootcamp program.
Participate in outreach, workshops, and related educational activities within CCE.
Perform other related job duties as assigned.
Basic Qualifications
PhD in chemistry, chemical engineering, materials science, computer science, or a closely related field.
Demonstrated expertise in machine learning and data science applied to problems in the chemical sciences.
Experience developing and implementing computational workflows for chemical data analysis or modeling.
Strong programming skills relevant to scientific computing and ML.
Experience teaching, mentoring, or training students and researchers.
Ability to work collaboratively with faculty, students, postdoctoral researchers, and administrative staff.
Strong written and oral communication skills.
High scientific rigor, creativity, and ethical standards.
Excellent organizational and time management skills, with the ability to manage multiple responsibilities.
Preferred Qualifications
Experience applying ML to molecular property prediction, reactions, catalysis, or spectroscopy.
Familiarity with deep learning architectures such as graph neural networks and generative models.
Experience with ML-accelerated electronic structure methods, molecular dynamics, or spectral analysis.
Experience with automation hardware or robotic platforms for chemical experimentation.
Background in curriculum development or educational program leadership.
Familiarity with best practices in data curation, model interpretability, and responsible AI use.
Required Documents
Resume