The Postdoctoral scholarship (2 years) within Optimization and Learning for Distributed Decision Systems at Umeå University offers a full-time research position for two years, with a starting date of 1 November 2026 or by agreement. The scholarship is hosted by the Department of Mathematics and Mathematical Statistics and is financed by the Kempe Foundation.

Overview

The Department of Mathematics and Mathematical Statistics conducts research in computational mathematics, discrete mathematics, mathematical modeling and analysis, geometry, mathematical statistics, and the mathematical foundations of artificial intelligence. The postdoctoral scholar will join the Mathematical Programming Group, which develops theory, methods, and software for large-scale optimization and decision problems, with applications in machine learning and data science. Key research areas include nonconvex optimization, stochastic optimization, distributed and federated optimization, operator splitting methods, and optimization with quantum computers.

The project explores how independent decision-makers can be coordinated toward a shared goal when their data, objectives, and constraints remain private. It models coordination as a bilevel optimization problem where local agents make their own decisions and a coordinating mechanism learns from these decisions to improve global performance. The researcher will have the opportunity to develop mathematical models, study theoretical properties, design algorithms, and explore applications in areas such as supply chains, energy systems, or multi-agent coordination.

Funding and Benefits

The scholarship is financed and administered by the Kempe Foundation. The stipend is tax-free and amounts to 750,000 SEK for two years, corresponding to 375,000 SEK per year.

Eligibility

• Doctoral degree: Applicants must have completed a doctoral degree (or a foreign degree deemed equivalent) no later than the time of the decision about the scholarship recipient. Priority is given to candidates who completed their doctoral degree no more than three years prior. Special reasons (e.g., illness, parental leave, military service) may allow earlier degrees.
• Field of study: Doctoral degree should be within a relevant subject area.
• Research experience: Documented experience in at least one of the following areas: optimization, machine learning, distributed or federated learning, control, operations research, or multi-agent systems.
• Language skills: Good ability to communicate research in written and spoken English.
• Desirable qualifications: Experience with bilevel optimization, distributed optimization, stochastic optimization, nonconvex optimization, first-order methods, operator splitting methods, privacy-preserving learning or optimization, or applications involving networked decision systems. Experience with numerical implementation and reproducible computational experiments is also a merit.
• Independence and collaboration: Ability to formulate research questions, structure research independently, and engage constructively with a collaborative, international research environment.

Application Process

A full application must include the following:

• Cover letter (maximum 2 pages) describing the applicant’s research background, motivation for applying, how previous experience relates to the project, and possible research directions.
• Curriculum vitae (CV) with a complete publication list.
• Verified copy of doctoral degree certificate or documentation clarifying when the doctoral degree is expected to be obtained.
• Verified copies of other diplomas, list of completed academic courses and grades.
• Copy of doctoral thesis and up to three relevant publications. For each selected publication, a brief explanation of its relevance and the applicant’s own contribution (especially for co-authored work).
• Other documents the applicant wishes to include.
• Contact information for two persons willing to act as references. References may be contacted later in the selection process.

The application should be written in English or Swedish, and attached documents should be in Word or PDF format. Applications must be submitted via Umeå University’s e-recruitment system Varbi by the deadline.

Deadline and Timeline

• Last application date: 31 July 2026
• First day of employment: 1 November 2026 or by agreement
• Published: 8 June 2026
• Reference number: FS 2.1.6-1248-26

Contact Information

For further details, contact Assistant Professor Alp Yurtsever at alp.yurtsever@umu.se.

More information about the department: https://www.umu.se/en/department-of-mathematics-and-mathematical-statistics/

Apply via the scholarship application system: https://umustipendie.varbi.com/en/apply/positionquick/944781/?where=39