Ledig stilling på Universitetet i Oslo

Blindern og Urbygningen (Foto: Wikimedia og Colourbox)
Blindern og Urbygningen (Foto: Wikimedia og Colourbox)

PhD Research Fellow in Experimental Nuclear Physics and Nuclear Astrophysics

Deadline: 19.09.2021

Universitetet i Oslo

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.


The research at the Department of Physics covers a broad range of subfields within physics and technology: From space research to medical physics. A good proportion of the research is interdisciplinary, and conducted in close cooperation with collaborators in Norway and abroad.


Education and teaching are other essential activities. We offer a broad range of courses, and the Department is involved in several study programmes at bachelor’s and master’s level. Some of the best lecturers in Norway are amongst our employees, and we are proud of our prizewinning teaching and learning environment. The Department has 200 employees, of which 50 are permanent scientific positions. On a yearly basis 20 students complete their Ph.D. and 50 finish their M.Sc. degree.

Job description

A position as PhD Research fellow in Experimental Nuclear Physics and Nuclear Astrophysics, with applications towards Bayesian Machine Learning is available at The Department of Physics.

The PhD position is connected to the research project “Dust from the Stars: Radiative Neutron Capture Rates Relevant to the Intermediate and Rapid Neutron-Capture Process” financed by the Research Council of Norway. The position will also be connected to the Center for Computational Science and Data Science (dScience) at the University of Oslo.

The PhD position will be for a period of three (3) years. Starting date preferably before November 1, 2021.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

More about the position

The aim of the PhD project is to obtain new information on the fundamental properties of atomic nuclei in hot, astrophysical environments, and the impact of these properties on neutron-induced reaction rates that are input for large-scale network calculations of heavy-element nucleosynthesis. Neutron-induced reactions relevant to the rapid neutron-capture process and the intermediate neutron-capture process are of particular interest.The PhD position involves both experimental and computational work. Specifically, the successful candidate will perform experiments at the Oslo Cyclotron Laboratory (OCL), Department of Physics, University of Oslo, to investigate moderately neutron-rich nuclei populated with the (alpha,p) reaction. Charged-particle–gamma coincidence data using the newly commissioned, state-of-the-art LaBr3:Ce detector array OSCAR will be analyzed with the so-called Oslo method.

On the computational side, the candidate is expected to work on new approaches to extract information from existing data from neutron resonance experiments to improve absolute normalization of the Oslo-method data away from stability. Here, possible avenues like machine learning (via Bayesian Neutral Networks and/or Gaussian Processes) are envisaged.

As the PhD position is part of a project with international partners (Michigan State University, USA, and Université Libre de Bruxelles, Belgium), short-term stays abroad can be expected during the PhD project.

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

  • Applicants must hold a Master's degree or equivalent in physics. A M.Sc. in experimental nuclear physics is strongly favored. Foreign completed degrees (at M.Sc. level) must correspond to a minimum of four years in the Norwegian educational system.
  • The candidate must be able to document solid programming skills.

Other preferred qualifications include:

  • Candidates with background in experimental nuclear physics will be strongly favored in the selection process, in particular candidates who have documented experience with large-volume scintillator detectors and particle-gamma coincidence measurements.
  • Knowledge and experience in high-performance computing and/or machine learning
  • A strong background and /or interest in statistics for physics applications

Personal skills

  • Good communication and collaboration skills
  • Ability to work in teams with a strong interdisciplinary profile

Grade and language requirements:

The norm is as follows:

  • the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
  • the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
  • the Master’s thesis must have the grade B or better in the Norwegian educational system
  • Fluent oral and written communication skills in English.

Please see the following link for more information regarding English requirements for applicants from outside of EU/EEA countries and exemptions from the requirements.

The purpose of the fellowship is research training leading to the successful completion of a PhD degree.

The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position. For more information see:

http://www.uio.no/english/research/phd/

http://www.mn.uio.no/english/research/phd/

We offer

  • Salary NOK 491 200 – 534 400 per annum depending on qualifications and seniority as PhD Research Fellow (position code 1017)
  • Attractive welfare benefits and a generous pension agreement
  • Vibrant international academic environment
  • Career development programmes
  • Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

How to apply

The application must include:

  • Cover letter - statement of motivation and research interests
  • CV (summarizing education, positions and academic work - scientific publications)
  • Copies of the original Bachelor and Master’s degree diploma
  • Transcripts of grades/records
  • Letters of recommendation
  • Documentation of English proficiency
  • List of publications and academic work that the applicant wishes to be considered by the evaluation committee
  • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

The application with attachments must be delivered in our electronic recruiting system (please follow the link “Apply for this job”). Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English or a Scandinavian language.

Interviews will be carried out as part of the hiring process.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

According to the Norwegian Freedom of Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

The University of Oslo aims to achieve a balanced gender composition in the workforce and to recruit people with ethnic minority backgrounds.

Contact information

For further information please contact:

  • Associate Professor Ann-Cecilie Larsen, e-mail: [email protected], Telephone: +47 95051841

For technical questions regarding the recruitment system, please contact HR Adviser Elin Thoresen, e-mail: [email protected], phone +47 22 85 71 96.

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