Postdoc in Machine Learning-Enhanced Thermodynamic Modeling of Alloys - Hiring in process/Finished, not possible to apply

Are you interested in working with dynamical mean field theory, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a postdoctoral position in machine learning approaches to dynamical mean field theory at Uppsala University.

The Department of Physics and Astronomy is one of the largest at Uppsala University, with almost 400 employees, of which about 120 are PhD students. The department conducts world-class research and education in both theoretical and experimental physics and has extensive collaboration with the outside world. The research is carried out at ten research divisions and covers everything from the unimaginably small to the large in areas such as energy supply, climate development, new materials and the universe. This entire spectrum is also reflected in the department's courses and training programmes. Around 2,500 students take undergraduate and graduate courses at the department every year. Read more on www.physics.uu.se

Uppsala University hereby declares the following position to be open for application: Postdoctoral position in electronic structure theory coupled to dynamical mean field theory, machine learning based many body physics and density functional theory.

Research area: Materials Theory. We are seeking a highly motivated postdoctoral researcher to join our team led by Prof. O. Eriksson at Uppsala University.

The Division of Materials Theory offers world-class research in solid-state theory, using both numerical and analytical methods. The research focuses on magnetism, electronic structures, topological phases, correlation phenomena, and materials for green energy.

Duties

The postdoctoral position involves work in a larger theoretical environment, focusing on magnetism, magnetization dynamics, spin-lattice simulations, ab initio theory for electronic structures, as well as theory for new functional materials. The research involves both numerical and analytical work on magnetic phenomena and many-body physics. A successful applicant is expected to have expertise in machine learning algorithms and dynamical mean-field theory. The successful candidate will be offered the opportunity to collaborate with leading experimental and theoretical groups at Uppsala University and other Swedish universities with a research focus on correlated electronic structures.

Requirements

PhD degree in physics, with good knowledge of solid-state theory, or a foreign degree equivalent to a PhD degree in physics. The degree needs to be obtained by the time of the decision of employment. Priority will be given to applicants who have completed their degree no more than three years before the deadline for applications.  Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

The following skills are requirements for the position:

• Experience with many-body theory and machine-learning calculations coupled to dynamical mean field theory.
• Excellent language skills in spoken and written English is a requirement.

The application should include a description of research interests, a CV, a list of publications, copies of degrees, and a copy of the dissertation if possible. Letters of recommendation may be attached to the application.

About the employment
The employment is a temporary position of two years according to central collective agreement. Starting date 1 November, 2025 or as agreed. Placement: Uppsala.

For further information about the position, please contact: Olle Eriksson, tel: +46-(0)18-4713625, email: olle.eriksson@fysik.uu.se.

Please submit your application by 27 October 2025, UFV-PA 2025/1354.

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