YRP PhD Projects 2024

The position focusses on exoplanet atmosphere and cloud formation processes. The project entails machine-learning modelling of the formation of cloud condensation nuclei by metal oxide clusters. The successful candidate will be part of Prof. Dr. Christiane Helling’s research group Exoplanet Climate & Weather at the IWF and  will be embedded in Young Researcher Program YRP@Graz. The candidate will collaborate with Prof. Markus Aichhorn and Prof. Robert Peharz of the Graz University of Technology and be part of our efforts to build a machine learning competence node at the IWF in Graz also by in cooperating  with the Graz Center For Machine Learning (GRAML).

Keywords: Exoplanet Atmosphere, Cloud Condensation Nuclei, Density Functional Theory, Machine learning Force Fields, Graph Neural Network.

Research Group Environment in the Graz area:   Exoplanet Climate & Weather / IWF & TU Graz (Prof. Dr. Christiane Helling), Exoplanet Characterisation and Evolution / IWF  (Doz. Dr. Luca Fossati), Planet-Forming Disks and Astrochemistry / IWF  (Dr. Peter Woitke), Computational Material Science / TU Graz  (Prof. Markus Aichhorn), Theoretical Computer Science /TU Graz (Prof. Robert Peharz).

Abstract: Space telescopes (e.g., JWST, PLATO, CHEOPS, and Ariel) and ground-based observations require substantial scientific modelling efforts to analyse their data. Cloud formation in the chemically diverse atmospheres of exoplanets has become a key obstacle to conclusively deriving the atmospheric compositions of extrasolar planets. We aim to leverage the potential of machine learning (ML) models to progress our understanding of exoplanet atmospheres by addressing one of the fundamental research questions of exoplanet climate research: How do clouds form in these chemically diverse atmospheric environments? This project aims to apply advanced ML models (e.g., Graph Neural Network) to study the formation of metal-oxide clusters as the base for modelling cloud condensation nuclei (CCN) formation for exoplanet atmospheres. CCN determines the cloud particle sizes and the gas phase depletion. We aim to answer critical scientific questions via our  ML-based cloud formation modelling. (a) What resolution in cluster space is needed to describe cluster properties accurately, (b) How higher computational efficiency outweighs cluster property uncertainties, and how to progress the application of ML technology in exoplanet astrochemistry. We will use high-precision thermodynamic cluster structures for small molecular species (i.e, TiO₂ [1, 2], V₂O₅ [3] ) and their isomers to train our ML methods to develop and test strategies to derive thermodynamic properties for underexplored cluster sizes beyond the training set.

Tasks:

• Learn about cloud formation as part of exoplanet climate modelling. 

• Learn about ab initio quantum mechanical calculations software (e.g., VASP, MLIP)

• Apply Machine Learning Force Field (MLFF) concept to existing metal oxide  (TiO₂, V₂O₅) cluster data to study their applicability for cloud formation modelling in exoplanet atmospheres.

• Apply MLFF calculation result to study the nucleation rate, and the resulting cloud structure for selected exoplanets (JWST or PLATO targets).

• Publish scientific results in peer-reviewed journals.  

The candidate will represent IWF at The James Webb Space Telescope (JWST) and PLAnetary Transits and Oscillations of Stars (PLATO) mission-related scientific collaboration forums and present results related to this project. 

References: 

[1] Sindel, J.P., Helling, Ch., Gobrecht, D., Decin, L. (2022). Revisiting fundamental properties of TiO₂ nanoclusters as condensation seeds in astrophysical environments, A&A 668, A35,https://doi.org/10.1051/0004-6361/202243306

[2] Sindel, J.P., Helling, Ch., Gobrecht, D., Chubb, K.L., Decin, L. (2023). Infrared spectra of TiO₂ clusters for hot Jupiter atmospheres, A&A, 680, A65,https://doi.org/10.1051/0004-6361/202346347

[3] Lecoq-Molinos, H., Gobrecht, D., Sindel, J.P., Helling, Ch., Decin, L. (2022). Vanadium oxide clusters in substellar atmospheres, A quantum chemical study, accepted to A&A, https://doi.org/10.48550/arXiv.2401.02784

The position focuses on energetic eruptions from our Sun. The PhD project entails data analysis and the application of machine-learning modelling for the analysis of large-scale solar prominence eruptions, coronal shock waves and their relation to the global 3D magnetic field environment. The successful candidate will be part of Prof. Astrid Veronig’s research group Solar and Heliospheric Physics at the University of Graz and will be embedded in the Young Researcher Program YRP@Graz. The candidate will collaborate with national and international partners of the EU Horizon project SOLER (Energetic Solar Eruptions: Data and Analysis Tools).

Keywords: Sun, Solar flares, Coronal mass ejections, Prominences, Deep Learning, ML.

Research Group Environment in the Graz area:   Solar and Heliospheric Physics / University of Graz (Prof. Dr. Astrid Veronig)

Abstract: The EU Horizon Europe project Energetic Solar Eruptions: Data and Analysis Tools (SOLER) will investigate the most energetic phenomena occurring at the Sun and provide new knowledge on their interrelations, variability and energy partitioning. Using the newly expanded and unprecedented heliospheric spacecraft fleet, the project will investigate energetic solar eruptions starting from three perspectives: fast coronal mass ejections (CMEs), strong X-ray flares, and large solar energetic particle (SEP) events. The main aim is to better understand how the eruptive phenomena are linked to each other, how they interact with each other, how they result in acceleration of high energy particles and their escape into interplanetary space. The project consortium consists of five European partner institutions: University of Turku (Finland; lead), University of Helsinki (Finland), University of Graz (Austria), Leibniz Institute for Astrophysics Potsdam (Germany), and Observatoire de Paris (France).

The announced PhD position will be part of the SOLER project. The specific aims are to study solar eruptions as observed by multi vantage-point heliospheric ESA and NASA missions, in particular Solar Orbiter, SDO and STEREO along with ground-based observations. The research focus will be 1) on the analysis of large-amplitude coronal waves and shocks caused by coronal mass ejections and their relevance for the production of Solar Energetic Particle (SEP) events, and 2) on the global modelling of the coronal magnetic field environment based on recently developed ML/Deep Learning methods for nonlinear force free field modelling (NLFFF).

Tasks:

• Develop tools for the analysis of large-amplitude waves and shocks propagating through the solar corona.

• Investigate well observed coronal shock waves in relation to their SEP production.

• Learn on ML (Deep Learning) methods, and use the newly developed global NLFFF code for modelling the 3D coronal magnetic field.

• Identify large-scale erupting filaments and eruptions globally connecting (transequatorial) over the two solar hemispheres and reconstruct their 3D magnetic field properties, along with detailed investigations of the eruption.

• Publish scientific results in peer-reviewed journals and present them at international conferences.

References: 

[1] Veronig, A.M., Podladchikova, T., Dissauer, K., et al. (2018). Genesis and Impulsive Evolution of the 2017 September 10 Coronal Mass Ejection, Astrophys. Journal 868, 107, https://doi.org/10.3847/1538-4357/aaeac5

[2] Jarolim, R., Thalmann, J., Veronig, A.M., Podladchikova, T. (2023).  Probing the solar coronal magnetic field with physics-informed neural networks, Nature Astronomy 7, 1171-1179.https://doi.org/10.1038/s41550-023-02030-9. Code available at : https://github.com/RobertJaro/NF2

[3] Wiegelmann, Th., Thalmann, J., Solanki, S. (2014). The magnetic field in the solar atmosphere, Astronomy and Astrophysics Review 22, 78.https://doi.org/10.1007/s00159-014-0078-7

This PhD research is designed to explore the interplanetary evolution of coronal mass ejections (CMEs) and their source regions on the Sun. The PhD project entails the analysis of imaging and in-situ plasma and field data as well as the application of state-of-the-art methods for magnetic field modelling. The successful candidate will be part of the research group Solar and Heliospheric Physics, led by Prof. Astrid Veronig, at the University of Graz and will be embedded in the Young Researcher Program YRP@Graz. The candidate will collaborate with national and international partners of the Austrian Science Fund (FWF) Principal Investigator Project “Magnetic helicity from the Sun to Earth” led by Dr. Julia K. Thalmann.
Keywords: Sun, Solar flares, Coronal mass ejections, Magnetic field modelling, Magnetic helicity.

Research Group Environment in the Graz area:   Solar and Heliospheric Physics / University of Graz (Dr. Julia K. Thalmann)

Abstract: The Austrian Science Fund (FWF) Principal Investigator Project “Magnetic helicity from the Sun to Earth” (Grant DOI: 10.55776/PAT7894023) led by Dr. Julia Thalmann is designed to investigate magnetic-field related properties, especially magnetic helicity, of interplanetary coronal mass ejections (ICMEs) from the Sun. For a full understanding, the combined analysis of the ICMEs measured in-situ by spacecraft at various locations in the heliosphere (in the form of magnetic clouds; MCs), their interplanetary evolution, as well as their solar source region is required. The main aim is to provide a more coherent picture of the physical properties of solar eruptions in interplanetary space, and especially in the near-Sun environment where they are largely unknown to date. The project will benefit from the collaboration with one national partner institute (Austrian Space Weather Office), one European (University of Zagreb) and one international (University of Stanford).

The PhD research will be carried out at the Solar and Heliospheric Physics research group at the Institute of Physics of the University of Graz, a world-leading research team on the physics of solar eruptions and their heliospheric evolution. The PhD project will be carried out in the framework of an FWF research project led by Dr. Julia K. Thalmann and will be embedded in the Young Researcher Program YRP@Graz. The PhD project will focus on the numerical modelling of magnetic field and the computation of magnetic helicity in solar eruptions and their interplanetary counterparts. The project will entail existing sophisticated numerical modelling schemes, partly relying on machine-learning approaches. The announced PhD study will cover in-depth studies of solar eruptions using data from NASA’s Solar Dynamics Observatory (SDO) satellite and will make use of unprecedented near-Sun data from Parker Solar Probe and Solar Orbiter.

Tasks:

•    Investigate well observed magnetic clouds (based on in-situ data) in context with their evolution as ICMEs (using imaging data) and their solar source region (using imaging data and magnetic field modelling).
•    Use state-of-the-art as well as newly developed machine-learning codes to model the 3D coronal magnetic field.
•    Identify and optimize the potential of existing tools to best approximate the magnetic field (and helicity), especially in the interplanetary regime.
•    Publish scientific results in peer-reviewed journals and present them at international conferences.

References: 

[1] Thalmann, J. K., Dumbovic, M., Dissauer, K., et al. (2023). Tracking magnetic flux and helicity from the Sun to Earth. Multi-spacecraft analysis of a magnetic cloud and its solar source, Astronomy & Astrophysics 669, A72, https://doi.org/10.1051/0004-6361/202244248

[2] Jarolim, R., Thalmann, J. K., Veronig, A.M., Podladchikova, T. (2023). Probing the solar coronal magnetic field with physics-informed neural networks, Nature Astronomy 7, 1171-1179,  https://doi.org/10.1038/s41550-023-02030-9. Code available at: https://github.com/RobertJaro/NF2

[3] Wiegelmann, T., Thalmann, J. K., Solanki, S. (2014). The magnetic field in the solar atmosphere, Astronomy and Astrophysics Review 22, 78,https://doi.org/10.1007/s00159-014-0078-7