PhD position in Statistics/ML at the Oslo Centre for Biostatistics and Epidemiology (OCBE)
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- Oslo
- Midlertidlig
- Fulltid
- 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.
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 “
- 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 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:
- 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.
- 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
- 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
- Opportunity of up to 1.5 hours a week of
- Full access to public health services through membership of the National Insurance Scheme.
- A reliable and generous pension agreement via the membership in the
- 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)