The Department of Mathematics and Mathematical Statistics offers a postdoctoral fellowship within the project “Improving Surgical Staffing with Data Driven AI Solutions”. The scholarship is full-time for two years starting January 2026, or as agreed.
Project description To meet the healthcare challenges of the future, resources must be used more efficiently than they are today. The combination of large-scale historical data and AI offers new opportunities to achieve this. The aim of this project is to develop data-driven planning and optimization tools for surgery and post-surgery units at Norrland University Hospital. Using statistical modelling and machine learning, we aim to create a digital twin of these units, which can then be used to optimize operations.
The work involves several specific challenges: processing times may be censored, outliers are common, and it is difficult to make strong model assumptions during optimization. Another clinically important challenge is adapting predictive models for use across different hospitals.
We are looking for a highly motivated individual with a strong interest in computational science and statistics, who would like to contribute to addressing important challenges in healthcare. Our research group works in an interdisciplinary environment, closely collaborating with the healthcare system.
The scholarship is funded and administered by the Kempe Foundations. The tax-free scholarship amounts to a total of 750,000 SEK, which corresponds to 31,250 SEK per month. There are also good opportunities for financing research costs.
Qualifications To qualify as a postdoctoral scholarship holder, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirement must be fulfilled no later than at the time of the decision about scholarship recipient. Priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree before that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area.
The doctoral degree should be in computational science, data science, mathematical statistics, statistics, optimization, or equivalent.
You should have experience working with statistical modelling and/or machine learning. Since the research language is English, you need to master the language both orally and in writing. You should also have good programming skills, preferably in R and/or Python.
Experience in interdisciplinary work, explainable AI (e.g., using SHAP values), imputation, variable selection, and feature extraction is considered an advantage.
Application A full application should include:
Cover letter, at most 2 pages, stating your motivation and highlighting experience relevant for the project,
Curriculum vitae (CV),
Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
Verified copies of other diplomas, list of completed academic courses and grades,
Copy of doctoral thesis. If the thesis is not available by the application deadline, then submit a summary of the thesis (at most 5 pages),
Publication list. For each article, briefly write your contribution, and provide a copy if it is not freely accessible online,
Email addresses and phone numbers of two people who can serve as references, where you indicate your relationship to each,
Other documents that the applicant wishes to refer to.
The application should be written in English or Swedish and attached documents should be in Word or PDF format. The application should be registered via Umeå University’s e-recruitment system Varbi and submitted by September 17, 2025.
Umeå University strives to offer an equal environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for this scholarship and especially encourage female applicants.
More information Further details are provided by Professor Patrik Rydén (patrik.ryden@umu.se, +46 70 482 3555).
More information about the department: www.umu.se/en/department-of-mathematics-and-mathematical-statistics/
