Postdoctoral Research Associate in Computational Chemistry, 
Machine Learning & Chemical Design

The Kostal Research Group at The George Washington University (GWU) is seeking 
a postdoctoral researcher to join a newly funded multi-institutional project 
developing computational frameworks for the de novo design of functional and 
safer chemicals. The GWU team leads the project's physics-based modeling effort, 
integrating quantum chemistry, molecular simulation, data science, and 
predictive modeling to develop mechanistically grounded relationships 
connecting molecular properties with chemical function, toxicity, 
bioaccumulation, and environmental degradation.
 
Successful candidate should have strong training in computational/theoretical 
chemistry and experience analyzing chemical or molecular datasets. 
Relevant expertise may include electronic-structure 
calculations, molecular simulation, chemoinformatics, QSAR/QSPR development and 
statistical modeling. Experience with machine learning, deep learning, 
generative AI, or AI-enabled molecular design is highly desirable. 
The position will involve close collaboration with experimental toxicology, 
AI/design and exposomics teams at partner institutions and provides 
an opportunity to work at the interface of fundamental computational 
chemistry, green chemistry, toxicology and emerging AI methods.
Applicants should hold, or expect to receive, a Ph.D. in computational chemistry 
or a closely related field. Strong quantitative skills, 
scientific independence, and an interest in interdisciplinary research, 
safer chemical design and mentorship of junior colleagues are essential.

Location: George Washington University, Washington, DC
Start date: Flexible; preference for an early start.

Please send a CV, brief description of research interests and relevant 
computational experience, and contact information for references 
to Prof. Jakub Kostal (jkostal]^[gwu.edu).