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PhD Research Fellow in Statistics
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 Department of Mathematics is part of the Faculty of Mathematics and Natural Sciences at the University of Oslo. The Department is engaged in teaching and research covering a wide spectrum of subjects within mathematics, mechanics and statistics. The research is on theory, methods and applications. The areas represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology, operator algebras, complex analysis and logic.
We have almost 50 persons in permanent academic positions and a large number of post docs and Ph.D. students. We also have an administrative and technical staff. The department represents a leading research environment in mathematical areas in Norway, and has a highly international profile.
About the position
Position as PhD Research Fellow in Statistics is available at the Department of Mathematics, Section for Statistics and Data Science.
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.
Starting date no later than October 1, 2024.
The fellowship period is three years. A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.
The position is attached to the Section for Statistics and Data Science at the Department of Mathematics, University of Oslo (UiO). This section consists of eight full time academic positions, nine adjunct positions and many PhD-students and postdocs, making up a group of more than 30. Statistics at UiO is internationally recognized and is a major part of a recently funded centre-of-excellence (INTEGREAT). INTEGREAT, which has a focus on knowledge driven machine-learning, is funded from the Research Council of Norway (RCN) for ten years, and will include a large number of PhDs and postdocs.
The successful applicant will join the new interdisciplinary research project "PLUMBIN’: Developing solvents for unclogging the calculational bottleneck in high-energy physics", which was recently financed by the RCN (2022-2029). This project is a collaboration between members of the Section for Statistics and Data Science, and the Section for Theoretical Physics at the Department of Physics, and aims at making powerful computational tools for exploring the fundamental constituents of the Universe.
The announced doctoral fellowship position will focus on investigating the properties of classical and higher-order asymptotic inferential tools in the non-regular settings related to the search for new particles in the high-energy physics framework. In such settings, the likelihood is not directly associated with the distribution of a random variable, but it is computed by combining different pieces of likelihood, not necessarily independent to each other and related to experiments different in their nature. The presence of many nuisance parameters complicates the situation. As a result, the coverage of the confidence intervals based on the classical likelihood ratio test may be far from the nominal one. Modifications of the likelihood and corrections to the likelihood ratio test must be investigated and adapted to the specific context.
We would also like to look at the quantification of uncertainty in higher-order quantum field theory calculations in high-energy physics. No prior knowledge of high-energy physics is required.
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.
- Master’s degree or equivalent in statistics. Master’s degrees in high-energy physics or other quantitative topics are also admissible, as long as a competence in statistics can be shown.
- Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system.
- A solid background in scientific computing, with programming skills in R or Python.
- Fluent oral and written communication skills in English.
- Good communication and collaboration skills, and the ability to work independently and in an interdisciplinary research environment.
Other desired qualifications include:
- Familiarity with the asymptotic theory framework.
- Experience with the use of pseudo-likelihoods and composite likelihoods.
- An interest in the application of statistics to high-energy physics problems.
Candidates without a Master’s degree have until June 30, 2024 to complete the final exam.
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
- 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:
- Salary NOK 532 200 – 575 400 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 and transcripts of records
- Documentation of English proficiency if applicable
- 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 with the best qualified candidates will be arranged.
Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.
According to the Norwegian Freedom and 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.
UiO has an agreement for all employees, aiming to secure rights to research results a.o.
Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.
If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.
For further information about the position please contact:
For questions regarding Jobbnorge, please contact HR Adviser Ole Rustad, phone: +47 22 85 13 87, e-mail: email@example.com
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