Postdoctoral Position in Molecular and Material Design

**Job Description**
The project aims to utilize advanced Machine Learning techniques to predict the anharmonic vibrational spectra of large Polycyclic Aromatic Hydrocarbon (PAH) molecules. These PAHs, with sizes exceeding 40 carbon atoms, are prevalent in astronomical environments and are responsible for dominant vibrational emission features observed in galaxy spectra. The current calculation methods for anharmonic spectra using 2nd order Vibrational Perturbation Theory on Density Functional Theory derived Quartic Force Fields are computationally intensive for astronomically relevant PAH sizes and numerous isomers, highlighting the need for machine learning solutions.

**Skills & Abilities**
• Demonstrated commitment as a researcher, evidenced by previous research experiences, publications, and presentations at international conferences.
• Experience with using neural networks and topological descriptors for molecules or materials.
• Excellent communication and writing skills in English.
• Ability to work both independently and collaboratively in a multidisciplinary environment.

**Qualifications**
Required Degree(s) in:
• Chemistry
• Physics
• Astronomy
• Computer Science
• Related field

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