Postdoc Position - ML Supported Cloud Formation Modelling

Postdoc Position - ML Supported Cloud Formation Modelling

Austrian Academy of Sciences

Graz, Austria

The successful candidate will be part of Prof Christiane Helling’s research group Exoplanets: Weather & Climate at the Space Research Institute (IWF) Graz. The project is conducted in collaboration with Prof Robert Peharz from the Graz University of Technology.

In this FWF funded project, we are interested in understanding cloud formation in exoplanets and specifically the formation of molecular cluster as pre-coursers of cloud formation in the diversity of extrasolar planets. We aim to explore advanced neural network architectures, particularly Graph Neural Networks (GNNs) and generative models, to predict the three-dimensional structures and thermo-chemical properties of large molecular clusters - tasks that are computationally prohibitive using traditional methods like Density functional theory (DFT) and molecular dynamics. Our modelling efforts support JWST and CHEOPS in physically interpreting observational data. We further contribute to science case studies and science preparation for PLATO, the high-energy space mission NewATHENA as well as HWO.

Your tasks:

  • Develop Neural Network models to predict three dimensional complex molecular cluster structures and thermo-chemical properties;
  • Software development and documentation;
  • Support scientific data interpretation (e.g., CHEOPS, JWST) and preparation for future missions;
  • Publication and support in proposal writing activities, and collaborate with group members.

Your profile:

Necessary to have:

  • PhD in computational chemistry, physics or astrochemistry, or computer science;
  • Practical experience in addressing ML-based research problems and experiences in programming;
  • Experiences in scientific publishing.

Beneficial to have:

  • Experiences in astrophysics and cloud formation;
  • Experience in advanced Neural Network models like GNNs, transformers.

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