Postdoctoral position

**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 over 40 carbon atoms, are prevalent in astronomical environments and are responsible for dominant vibrational emission features in galaxy spectra. The computational intensity of calculating anharmonic spectra using 2nd order Vibrational Perturbation Theory on Density Functional Theory derived Quartic Force Fields for such large molecules and numerous isomers necessitates the application of machine learning.

**Skills & Abilities**
• 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

**Experience**
Other:
• Committed researcher, demonstrated by previous research experiences, publications, and presentations at international conferences

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