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New condensed matter physics experiments enabled by machine learning

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 February 2025 or later.

Title:
New condensed matter physics experiments enabled by machine learning

Research area and project description:
Machine learning techniques are starting to revolutionize the way we do science. They are especially helpful for making sense of huge and complex data sets generated by new types of experiments. So far, most applications of machine learning have been focused on analyzing existing experimental data and the question thus arises if machine learning could also enable new ways of collecting experimental data in the first place.

This question is central to the present PhD project. The broader task is to integrate machine learning techniques into the data collection in an angle-resolved photoemission spectroscopy experiment on the synchtrotron radiation source ASTRID2 in Aarhus. The PhD student will enable new types of measurements by merging the current data collection tools with machine learning procedures, and demonstrate the feasibility of the approach by photoemission experiments on novel quantum materials. The eventual objective will be to enable new types of experiments that can unravel the complex physics in quantum materials. The project is thus situated on the border between experimental physics and data science.

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 must hold a relevant Master’s degree in physics or a related discipline. They need to have a strong interest in computer science and experience in coding. Experience in software controlling experiments in desirable.

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, 8000 Aarhus C, Denmark. 

Contacts:
Applicants seeking further information for this project are invited to contact: Professor Philip Hofmann, philip@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 September 2024)

  1. Choose November 2024 Call with deadline 1 November 2024 at 23:59 CET.
  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: “New condensed matter physics experiments enabled by machine learning (Ncmpee)”

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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