26.09.23 Computational Chemistry Postdoc

Computational Chemistry List, Ltd; Washington, Northern (District of Columbia, KY); Hybrid; USD 52,000 - 64,000; Full time

Job summary

The Kostal Research Group at George Washington University is seeking a Postdoctoral Research Associate to join a multi-institutional project on computational design of functional and safer chemicals. The role blends quantum chemistry, molecular simulation, data science, and predictive modeling to link molecular properties with function, toxicity, and environmental fate.

Applicants should hold a Ph.D. in computational chemistry or related field and have strong quantitative skills, independence,

Qualifications

• PhD or expected PhD in computational chemistry or related field.
• Strong training in computational/theoretical chemistry and data analysis.
• Experience with ML/AI methods in chemistry is highly desirable.

Responsibilities

• Develop computational frameworks for de novo design of chemicals.
• Collaborate with toxicology, AI/design and exposomics teams.
• Mentor junior colleagues and contribute to interdisciplinary research.

Skills

Computational chemistry

Machine learning

Data analysis

Python

Education

PhD in computational chemistry or related field

Tools

Electronic-structure calculations

Molecular simulation

QSAR/QSPR

Job description

https://server.ccl.net/cca/jobs/joblist/mess0070344.shtml

CCL 26.09.23 Computational Chemistry Postdoc

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.