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Postdoctoral Fellow
Postdoctoral Research Fellow Part-time
Project Duration: August 2025–July 2026
Project Overview: We invite applications for a postdoctoral researcher to contribute to an innovative AI/ML research initiative. The project integrates cyber twin protocols—originally developed for industrial process optimization—with advanced quantum chemical methods to map noisy Generalized Quantum Dot (GQD) spectral data to predicted chromophore structures.
Our work enhances hybrid TD-PiFCI+DFT modeling to produce reliable NIR and XPS spectra, addressing real-world challenges such as experimental noise and simulation uncertainty. This is a highly interdisciplinary project combining physical chemistry, machine learning, and data science.
Researchers from diverse backgrounds with a passion for AI-powered scientific discovery and computational Chemistry are encouraged to apply.
Key Responsibilities
Preprocessing and anomaly detection of spectral data
Spectral simulation using TD-PiFCI and DFT methods
Machine learning model development (e.g., Gaussian Process Regression, Random Forests, SHAP)
Scientific documentation, reporting, and publication preparation
Participation in collaborative meetings and weekly project planning
Mentoring junior researchers, where appropriate
Preferred Qualifications
Background: Chemistry, Physics, Electrical/Computer Engineering, Computer Science, AI/ML, Quantum Modeling
Skills:
Programming in Python (especially with scikit-learn, PyTorch, GPy)
Experience with DFT or post-Hartree–Fock methods
Strong analytical, writing, and communication skills
Self-motivated and interdisciplinary research mindset
Application Process
To apply, please email the following materials to Dr. Rana:
Curriculum Vitae (CV)
One-page weekly research activity plan
[Please click the Apply button for the link or address]
Final selection will be based on a written exam and interview. Please note: this advertisement is faculty-initiated and will undergo formal university approval following the candidate selection.