Manuela Zucknick

The University of Oslo invites applications for a 3-year PhD Fellowship in Biostatistics at the Oslo Centre for Biostatistics and Epidemiology (OCBE), Institute of Basic Medical Sciences. OCBE is one of Europe's most active biostatistics centres, internationally recognized for its research in biostatistics, machine learning, and epidemiology, and maintains numerous collaborations with leading biomedical research groups both in Norway and internationally. The successful candidate will join the research group 'Statistical learning in molecular medicine' and participate in the T-PRESS consortium, which aims to support trustworthy personalized healthcare decisions. The PhD project, entitled “Reliable Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions in the T-PRESS Evidence Ecosystem Framework,” focuses on developing Bayesian statistical and machine learning methods for treatment response prediction in cancer, specifically using adjuvant immunotherapy for renal cell carcinoma as a use case. The research will integrate clinical information, molecular tumor characterizations, and in vitro drug response experiments with patient-derived organoids (PDOs) to provide personalized risk assessments and predictions for treatment effect, including explicit uncertainty estimates. Key research questions include adapting statistical models for drug response, integrating heterogeneous clinical and multi-omics data, evaluating the predictive value of organoid data, and validating models for trustworthy clinical decision support. The PhD program at the University of Oslo is designed for research training leading to a PhD degree in medicine and health sciences. Candidates are expected to publish several papers in leading scientific journals and complete a small number of advanced courses as part of their doctoral training. Admission to the doctoral program must be approved within three months of appointment. Applicants must hold a master's degree in biostatistics, bioinformatics, statistics, mathematics, computer science, or a related quantitative field with proven competence in statistics. Ideal candidates will have a strong background in statistical methodology, especially Bayesian statistics and statistical learning for high-dimensional data, solid programming skills (R or Python), and a keen interest in interdisciplinary research involving molecular biology and cancer. English proficiency is mandatory; Norwegian language skills are not required. The University of Oslo values diversity and inclusion and encourages applicants from varied backgrounds, including those with disabilities or CV gaps. The position offers a stimulating international research environment, meaningful tasks contributing to societal development, good welfare schemes, and career development opportunities. Salary ranges from NOK 550,800 to 595,000 per year, with membership in Statens Pensjonskasse providing additional benefits. Applications must be submitted via Jobbnorge, including a cover letter, CV, educational certificates and transcripts, documentation of English proficiency (if applicable), list of publications (if applicable), and 2-3 references. All documentation should be in English or a Scandinavian language. The deadline for applications is 17th May 2026. For questions about the position, contact Professor Manuela Zucknick at [email protected]. For more information about the University of Oslo and OCBE, visit uio.no .

The University of Oslo invites applications for a 3-year PhD Fellowship in Biostatistics at the Oslo Centre for Biostatistics and Epidemiology (OCBE), Institute of Basic Medical Sciences. OCBE is one of Europe's most active biostatistics centres, internationally recognized for its research in biostatistics, machine learning, and epidemiology, and hosts about 75 researchers. The centre collaborates with leading biomedical research groups both nationally and internationally and is a partner in the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) and the Norwegian Centre for Trustworthy AI (TRUST). The successful applicant will join the research group 'Statistical learning in molecular medicine' and participate in the T-PRESS consortium, which aims to support trustworthy personalized healthcare decisions. The PhD project, titled 'Reliable Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions in the T-PRESS Evidence Ecosystem Framework', focuses on developing Bayesian statistical and machine learning methods for treatment response prediction in cancer, specifically using adjuvant immunotherapy for renal cell carcinoma as a use case. The research will integrate clinical information, molecular tumor characterizations, and in vitro drug response experiments with patient-derived organoids (PDOs) to provide personalized risk assessments and predictions for treatment effect, including explicit uncertainty estimates. Key research questions include adapting statistical models to account for biological and technical variability in PDOs, integrating heterogeneous clinical and multi-omics data, assessing the added predictive value of organoid data, and validating prediction models for trustworthy integration into digital decision aids at the point of care. The PhD program requires admission to the doctoral degree program at the Faculty of Medicine, with the expectation to complete the project within the fellowship period. The thesis typically includes several papers published in leading scientific journals, and candidates must take a small number of advanced courses as part of their training. The University of Oslo offers an ambitious and international research environment, meaningful tasks, good welfare schemes, career development opportunities, and membership in Statens Pensjonskasse, one of Norway's best pension schemes. Applicants must hold a master's degree in biostatistics, bioinformatics, statistics, mathematics, computer science, or a related quantitative subject with proven competence in statistics. Ideal candidates have a strong background in statistical methodology (especially Bayesian statistics and statistical learning for high-dimensional data), solid programming skills (R or Python), and a strong interest in interdisciplinary research with applications in molecular biology and cancer research. English proficiency is mandatory; Norwegian is not required. The University of Oslo is committed to equality, inclusion, and diversity, and encourages applicants from diverse backgrounds. Salary for the position ranges from NOK 550,800 to 595,000 per year, depending on competence and experience, with a 2% deduction for statutory contributions to the State Pension Fund. The application should include a cover letter, CV, educational certificates and transcripts, documentation of English proficiency (if applicable), list of publications (if applicable), and 2-3 references. Applications must be submitted via the Jobbnorge recruitment system. The deadline for applications is 17th May 2026. For further information, contact Professor Manuela Zucknick at [email protected].

OCBE – Oslo Centre for Biostatistics and Epidemiology at the University of Oslo is advertising an open fully funded 3-year PhD fellowship in Biostatistics . The project is titled “Reliable Bayesian prediction models with uncertainty quantification for trustworthy personalized treatment decisions” . This is a strong fit for applicants interested in statistical methodology, Bayesian modelling, prediction models, uncertainty quantification, and applications to personalized medicine and treatment decision-making. The announcement is posted by Professor Manuela Zucknick , Director of OCBE, University of Oslo and Oslo University Hospital. The post indicates that the position is still open and that the deadline is approaching fast. Funding: fully funded 3-year PhD fellowship. Deadline: May 17. How to apply: use the application link provided in the post and follow the instructions in the official job advertisement. The linked job page is titled “PhD position in Biostatistics at the Oslo Centre for Biostatistics and Epidemiology (OCBE)” at the University of Oslo.