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PhD Position in Experimental Low Energy Particle Physics at the University of Bern University of Bern in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Fixed-term 100% PhD position; funding/stipend details are not stated in the post.
Country
Switzerland
University
University of Bern

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About this position
PhD opportunity in Experimental Low Energy Particle Physics at the University of Bern, working with the Fundamental Neutron and Precision Physics Group at the Albert Einstein Center for Fundamental Physics (AEC) and the Laboratory for High Energy Physics (LHEP).
The project is part of the n2EDM experiment, which searches for the neutron electric dipole moment and probes physics beyond the Standard Model and new sources of CP violation. The position includes regular experimental work at the Paul Scherrer Institute (PSI) in Villigen, Switzerland, where the experiment is operated.
Research tasks focus on data analysis, statistical studies, Monte Carlo simulations, and the quantitative investigation of systematic effects. The student will also take part in data-taking shifts, experiment operation and monitoring, and related experimental activities at PSI.
Eligibility: applicants should hold or expect to obtain an MSc degree in physics. A strong interest in experimental physics, precision measurements, data analysis, and computational methods is expected. Programming experience, Monte Carlo simulation skills, and statistical data analysis are advantageous.
Application: submit a CV, short motivation letter, academic transcripts, and names of possible references to [email protected]. The selection is on a rolling basis and the position remains open until filled. Start date is flexible and arranged with the successful candidate.
Funding details
Fixed-term 100% PhD position; funding/stipend details are not stated in the post.
What's required
Applicants should hold or expect to obtain an MSc degree in physics. A strong interest in experimental physics, precision measurements, data analysis, and computational methods is expected. Experience with programming, Monte Carlo simulations, and statistical data analysis would be an advantage.
How to apply
Send a CV, short motivation letter, academic transcripts, and the names of possible references by email to [email protected]. Applications are reviewed on a rolling basis until the position is filled.
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