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Grain surface reactions in astrochemistry with machine learning interatomic potentials

Applications are invited for a PhD fellowship/scholarship at Graduate School of Natural Sciences, Aarhus University, Denmark, within the Physics and Astronomy programme. The position is available from August 2026 or later. 

Title:
Grain surface reactions in astrochemistry with machine learning interatomic potentials 

Research area and project description:
Within the Center for Interstellar Catalysis at the Department of Physics and Astronomy, we have an exciting opening for a PhD position supervised by Assoc. Prof. Mie Andersen. The PhD candidate will develop machine learning interatomic potentials to study grain surface reactions in astrochemistry.

The project focuses on silicates, which are a major constituent of dust grains in interstellar gas clouds. The reactivity of realistic silicate grain surfaces is poorly understood, since the grains may be amorphous, contain varying amounts of Mg and Fe, and be fully or partly covered in water-rich ices. This complexity is challenging to capture with first-principles methods like density functional theory (DFT), where the computational cost typically limits us to simple model catalyst surfaces and simplified reaction networks. 

In this project, the PhD candidate will develop graph neural network (GNN) interatomic potentials based on DFT calculations to be employed in connection with structure optimization methods and reaction exploration. Realistic structures of silicate surfaces will be identified and used as the starting point for exploring reactions of astrochemical interest. The exact reaction paths will be guided by findings from experimental partners in the center and could include top-down chemistry such as bond-breaking in N-substituted polycyclic aromatic hydrocarbons (PAHs) or bottom-up chemistry such as reactions of smaller N-containing hydrocarbons. These reactions may be a starting point for the formation of complex organic molecules, e.g. nucleobases, of relevance to prebiotic chemistry. GNN potentials will also be used to calculate IR spectra for comparison to lab or observational data.

The PhD candidate will benefit from a supportive and inspiring international environment and collaborations with partners across theory, laboratory experiments and astronomical observations within the Center for Interstellar Catalysis.

More information here:

https://phys.au.dk/forskning/forskningsomraader/catalytic-structure-activity-relationships-with-machine-learning

https://phys.au.dk/intercat

For technical reasons, you must upload a project description. When - as here - you apply for a specific project, please simply copy the project description above, and upload it as a PDF in the application. If you wish to, you can indicate an URL where further information can be found.

Qualifications and specific competences:
Applicants to the PhD position must have a Master’s degree in Physics, Chemistry, Nanoscience or related. If applying for a 4+4 PhD position, the applicant must have a Bachelor of Science degree and be one year into the Master’s program.

Experience with computer programming (e.g. Python) is required. Experience with first-principles calculations and/or machine learning methods is not required but will count positively in the assessment. Explicit knowledge of astrochemistry is not required.

Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Physics and Astronomy, Ny Munkegade 120, DK-8000 Aarhus C, Denmark. 

Contacts:
Applicants seeking further information for this project are invited to contact: 
Associate Professor, Mie Andersen, mie@phys.au.dk


How to apply:

For information about application requirements and mandatory attachments, please see the Application guide. Please read the Application guide thoroughly before applying.

When ready to apply, go to https://phd.nat.au.dk/for-applicants/apply-here/ (Note, the online application system opens 1 March 2026)

  1. Choose May 2026 Call with deadline 1 May 2026 at 23:59 CEST.
  2. You will be directed to the call and must choose the programme “Physics and Astronomy”.
  3. In the boxed named “Study”: In the dropdown menu, please choose: “Grain surface reactions in astrochemistry with machine learning interatomic potentials (Gsraml)” 

Please note:

  • The programme committee may request further information or invite the applicant to attend an interview.

At the Faculty of Natural Science at Aarhus University, we strive to support our scientific staff in their career development. We focus on competency development and career clarification and want to make your opportunities transparent. On our website, you can find information on all types of scientific positions, as well as the entry criteria we use when assessing candidates. You can also read more about how we can assist you in your career planning and development.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background.

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