Marie Eriksson

Umeå University, one of Sweden’s largest and most dynamic higher education institutions, is renowned for its world-leading research and high-quality education. The Department of Statistics at the Umeå School of Business, Economics and Statistics (USBE) is inviting applications for a fully funded PhD position in Statistics, focusing on the development of novel statistical methods for causal inference using machine learning and big datasets. This position is part of the WASP-HS project, 'Machine learning to study causality with big datasets: towards methods yielding valid statistical conclusions,' led by Professor Xavier de Luna and Tetiana Gorbach. The project aims to advance statistical inference on causal effects by leveraging machine learning algorithms and large-scale data, contributing to the Stat4Reg research environment. As a PhD student, you will have access to Umeå University's supercomputing facilities and unique data infrastructure, including comprehensive socioeconomic and health data covering the entire Swedish population from 1960 to the present. This environment offers exceptional opportunities for interdisciplinary research and collaboration. The PhD position is fully funded for four years, with the possibility of teaching or consulting duties up to 20% of your time, which may extend the program duration to ensure four years of graduate studies. The starting date is March 1, 2026, or as agreed, with the latest possible start date being November 1, 2026. Applicants should hold an advanced degree with a major in Statistics or equivalent qualifications and have completed at least 30 ECTS credits in Mathematics. Experience with R programming or similar languages and familiarity with machine learning methods are considered advantageous. The selection process will assess your academic qualifications and potential to benefit from doctoral-level education. To apply, submit your application via the Umeå University recruitment system by January 6, 2026. Your application should include a motivation letter, CV, completed 'New PhD' form, copies of undergraduate and graduate theses, degree certificates, and contact details for at least two referees. Non-EU/EEA applicants must ensure they have a valid residence permit before the study start date. For further information, contact Professor Xavier de Luna ([email protected]), PhD Tetiana Gorbach ([email protected]), or Professor Marie Eriksson ([email protected]). More details about the doctoral program and the department can be found on the university’s website. Umeå University fosters a collaborative and open academic culture, with a strong commitment to sustainability and societal development. The Department of Statistics is part of a vibrant research community, offering excellent resources and support for graduate students. Join us to contribute to cutting-edge research in statistical science and machine learning, and be part of a university that shapes the future.

Umeå University, one of Sweden’s largest and most dynamic higher education institutions, is renowned for its world-leading research and high-quality education. The Department of Statistics at the Umeå School of Business, Economics and Statistics (USBE) is inviting applications for one or two fully funded PhD studentships in Statistics, focusing on methodological development and applied register-based health research. The university is internationally respected, nationally influential, and regionally rooted, with a strong commitment to societal development and sustainable growth. The PhD projects are led by Professor Marie Eriksson and Associate Professor Anita Lindmark, and are closely related, addressing major population diseases such as stroke and infectious diseases. The research is based on analyses of large-scale Swedish register data and aims to develop generalizable statistical methods for register-based health research. The projects will contribute new knowledge on risk, prognosis, and underlying mechanisms in complex disease processes. One project centers on predictive modelling, utilizing machine learning and deep learning to develop and evaluate risk measures and models that accurately identify patients and patient groups at increased risk of severe disease outcomes. For selected patient subgroups, medical imaging data will be integrated into the models. The second project focuses on causal mediation analysis, aiming to advance statistical methods that investigate why disease risks and health inequalities arise when multiple interrelated mechanisms are involved. This project combines the handling of multiple mediators with causal inference and modern machine-learning approaches. The PhD position is fully funded for four years, with the possibility of appointment to statistical consulting, teaching, or other duties up to 20% of the time, which may prolong the program duration to guarantee four years of graduate studies. The starting date is September 1, 2026, or upon agreement, with the latest possible start date being December 15, 2026. Applicants must have a degree awarded at the advanced level with a major in Statistics or equivalent qualifications meeting the national requirements for admission to doctoral studies in Sweden. Additionally, applicants must have satisfactorily completed courses in Mathematics equivalent to at least 30 ECTS credits. Experience in R programming, mediation analysis, machine learning, and analysis of large-scale health register data is considered a merit. Assessment is based on qualifications and the ability to benefit from doctoral-level education. To apply, submit your application via the university recruitment system by May 28, 2026. The application should include a letter of motivation describing your research interests and relevance to the position, a CV, the completed 'New PhD' form, copies of undergraduate and graduate theses, relevant degree certificates, and contact details for at least two referees. For further information, contact Professor Marie Eriksson ([email protected]) or Associate Professor Anita Lindmark ([email protected]). Umeå University offers a vibrant academic environment, cohesive campuses, and a culture that promotes collaboration and knowledge exchange. The Department of Statistics conducts research in statistical sciences, both method development and empirical research, in collaboration with other disciplines. USBE is AACSB-accredited and sustainability certified according to ISO14001. More information about doctoral studies and the department can be found at the provided links.