About the position
We invite applications for a three-year position as PhD Research Fellow in statistics available at the Oslo Centre for Biostatistics and Epidemiology (OCBE), Department of Biostatistics, Institute of Basic Medical Sciences (IMB), University of Oslo (UiO), Norway.
Starting date no later than September 1st, 2026 (or as soon as possible). The fellowship period is three years. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.
Place of work is the Department of Biostatistics (OCBE), Domus Medica, Gaustad UiO campus, Oslo.
Job description
The position is connected to the project “Bayesian Enhanced Tensor Factorization Embedding Structure (BETTER)”, and this PhD project specifically aims at developing a unified, scalable, and interpretable framework for tensor analysis. Specifically, the project will:
- Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models.
- Account for spatial structures, physical laws, high-dimensional imaging, and clinical covariates.
- Apply these methods to spatial transcriptomics and fluorescence imaging data to gain a more precise understanding of complex biological systems.
Research Environment & Collaboration
The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods, the candidate will be positioned at the forefront of genetic data science.
- Local Research Infrastructure: You shall take part in the research group on “Statistical models for high-dimensional and functional data”, led by Professor Valeria Vitelli at OCBE, and will actively collaborate on data analyses and research problems with the MolMed Imaging Platform at IMB.
- Global Impact: You will join the FunGen-AD consortium, the world’s largest research initiative studying the genetic underpinnings of Alzheimer’s disease.
- International Mobility: The position includes a 3 to 6-month research stay at Columbia University in New York (USA).
- Publication: Candidates are encouraged to publish in top-tier venues across machine learning (e.g., NeurIPS, ICML), statistics, and computational biology.
- Dual Affiliation: The position will be based at and affiliated with the University of Oslo (Norway) and will be also affiliated with Columbia University (USA).
The research group on statistical models for high-dimensional and functional data is part of the larger and active research environment on “High-dimensional statistics” at OCBE. OCBE has expanded considerably during the last decade, becoming one of Europe's most active internationally recognized biostatistics groups with currently over 70 researchers. This PhD position is also embedded in an international research environment with co-supervision across statistics and machine learning. You will be encouraged to collaborate with prestigious US scholars at University of Columbia and other affiliated universities within the FunGen-AD consortium.
This therefore is a unique opportunity to contribute to cutting-edge research in statistics and machine-learning, by developing innovative methods at the interplay between theoretical and computational aspects, within a collaborative and supportive academic environment. You will be part of a dynamic group of early career researchers, supervised by two main PIs and senior experts from diverse fields of application.
What skills are important in this role?
Required qualification
The Faculty of Medicine 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, machine learning, mathematics, computer science, physics, or a closely related quantitative discipline. In case of a foreign completed degree (M.Sc.-level), this must correspond to a minimum of four years in the Norwegian educational system. The Master’s degree must be B or better in the Norwegian educational system
- The Master project should treat methodological aspects with mathematical tools. The candidate must show a strong interest in method development.
- Proven competence in probability, linear algebra, and statistical modelling are essential for this position.
- Demonstrated strong proficiency in programming (e.g., Python, PyTorch/JAX, or similar) and computational skills are required for this position.
- Candidates must have excellent interpersonal and communication skills. Personal suitability and an interest in the themes connected to the funded project will be emphasized.
- Working language in the group and at OCBE is English, hence excellent communication skills in written and oral English are a prerequisite. English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8
Candidates without a master’s degree have until 31.08.2026 to complete the final exam. The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/
All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation. To be admitted to the PhD programmes at the University of Oslo, an applicant must have a five year master's degree or equivalent studies that have been recognised by the faculty as forming a sufficient basis for admission.
Desired qualifications
- Some background knowledge in either (computational) Bayesian methods, or statistical learning for complex data, unsupervised learning, or matrix factorization, is an advantage.
- Experience with management and analysis of large datasets is an advantage.
- Experience with biomedical applications is an advantage.
- Experience with interdisciplinary collaborations is an advantage.
Personal skills
The successful candidate is expected to:
- Demonstrate analytical ability and intellectual curiosity
- Be highly motivated for theory-driven, foundational research
- Show persistence and creativity when tackling technically challenging problems
- Work independently while collaborating effectively in an interdisciplinary team
- Have strong ambitions for an academic or research-oriented career in machine learning, statistics or computational biology
- Show ability to work in a structured manner and swiftly adapting to new tasks
- Show good communication and collaboration skills
- Show a positive attitude towards and the ability to handle hectic periods
Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including skills.
We need different perspectives in our work
UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no.
We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues—could you be the next one?
We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures.
If you have an immigrant background, a disability, or CV gaps, we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian).
The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports.
More information about gender equality initiatives at UiO can be found here.
We hope you will apply for the position with us.
We can offer you
- Salary in position as Doctoral Research Fellow, position code 1017 in salary range NOK from 550 800 to 600 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund.
- A friendly professional and stimulating international working environment at OCBE, with committed colleagues that care and help each other. Special focus is also given to newly employed personnel relocating from abroad, with a dedicated central office at UiO for international relocation.
- Exciting and meaningful tasks in an organization with an important societal mission, contributing to knowledge development, education, and enlightenment that promote sustainable, fair, and knowledge-based societal development.
- A workplace with good development and career opportunities. Access to a network of top-level national and international collaborators.
- Good welfare schemes. Read more about the benefits of working in the public sector at Employer Portal.
- Annual paid leave for 5 weeks, plus public holidays.
- Opportunity of up to 1.5 hours a week of exercise during working hours.
- Full access to public health services through membership of the National Insurance Scheme.
- A reliable and generous pension agreement via the membership in the State Pension Found, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes.
- Career development programmes
How to apply
Your application must include:
- Cover letter - statement of motivation and research interests
- CV (summarizing education, positions and academic work - scientific publications)
- Transcripts of records, copies of the original Bachelor’s and Master’s degree diploma (see below)
- Documentation of English proficiency if applicable
- List of publications and academic work that the applicant wishes to be considered by the evaluation committee
- The master thesis or at least some finished chapter of the master thesis
- Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)
Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for the position".
When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language.
General information
The best qualified candidates will be invited for interviews.
Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we cannot, you will hear from us.
Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.
The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.
Om arbeidsgiveren:
The University of Oslo is Norway’s oldest and highest ranked educational and research institution, with 26 500 students and 7 200 employees. With its broad range of academic disciplines and internationally recognised research communities, UiO is an important contributor to society.
The Institute of Basic Medical Sciences overall objective is to promote basic medical knowledge in order to understand normal processes, provide insight into mechanisms that cause illness, and promote good health. The Institute is responsible for teaching in basic medical sciences for the programmes of professional study in medicine and the Master's programme in clinical nutrition. The Institute has more than 300 employees and is located in Domus Medica.