Doctoral Researcher, Computational Uncertainty Quantification, Faculty of Science - Hiring in process/Finished, not possible to apply

We are now looking for

Doctoral Researcher

in Applied Mathematics: Sparse Measurement Strategies for Goal-Oriented Inverse Problems, Faculty of Science, Research Unit of Mathematical Sciences.

The position is part of the SPARSe Academy Fellowship project: “Strategic Planning and Analysis for Reduced Sensing in Inverse Problems” and is connected to the FAME Flagship – Flagship of Advanced Mathematics for Sensing, Imaging and Modelling.

The position is located in the Research Unit of Mathematical Sciences, which has a strong international profile in inverse problems, applied mathematics, computational mathematics, and uncertainty quantification.

About the project

Inverse problems arise in many areas of science and technology, including medical imaging, geophysical imaging, industrial sensing, and astronomical imaging. Traditional approaches usually reconstruct a full image or field first, and then extract the relevant information, such as a tumour boundary, geological interface, or material defect, in a post-processing step.

This project takes a different approach: instead of reconstructing everything, we aim to infer the Quantity of Interest directly from sparse and strategically selected measurements. The central idea is that many relevant quantities in inverse problems have low-dimensional geometric structure, such as curves, surfaces, or interfaces. These can be described using manifold-based models, Bayesian uncertainty quantification, and computational methods for partial differential equations.

The doctoral researcher will contribute to the development of mathematical and computational methods for:

• direct inference of low-dimensional Quantities of Interest in inverse problems
• uncertainty quantification for manifold-based models
• sparse and optimal measurement strategies
• numerical algorithms for Bayesian inverse problems
• applications in X-ray computed tomography and/or seismic imaging

The project combines applied mathematics, numerical analysis, probability, inverse problems, and computational modelling. It has strong links to real-world applications in medical imaging and geophysical imaging.

Research environment

The doctoral researcher will work under the supervision of Assistant Professor Babak Maboudi Afkham in the Inverse Problems Group at the University of Oulu. The project will be carried out in close connection with the FAME Flagship and the broader Finnish inverse problems research community.

The doctoral researcher will join an active, international, and collaborative research environment with expertise in inverse problems, uncertainty quantification, computational mathematics, mathematical imaging, and applied analysis. The project also includes collaboration opportunities with national and international partners in applied mathematics, medical imaging, and geophysics.

What we offer

• We offer a unique opportunity to work on a mathematically rich and application-driven PhD project at the interface of inverse problems, uncertainty quantification, and computational mathematics.

  The position offers:

  • supervision in an internationally active inverse problems research group
  • a clear three-year PhD project connected to a funded Academy Fellowship and FAME Flagship research environment
  • opportunities for international collaboration
  • access to modern computational resources, including national high-performance computing infrastructure
  • opportunities to contribute to open-source scientific software
  • a supportive and flexible working culture. Read more about working with us.
  • the possibility to develop expertise in both theory and computational applications
  • Access to sports, culture, and well-being benefits (ePassi). Read more about other staff benefits. 

  Living and working in Oulu

  Oulu is a highly livable city in northern Finland, offering an excellent environment for international researchers. The city combines a strong technology and research ecosystem with a calm, safe, and nature-rich lifestyle.

  Oulu offers:

  • excellent work-life balance
  • safe and family-friendly living conditions
  • extensive cycling routes and public sports facilities
  • easy access to forests, lakes, the sea, and northern nature
  • opportunities for skiing, hiking, biking, swimming, climbing, and other outdoor activities
  • a growing international communit
  • reliable public services, healthcare, and education

  For researchers who enjoy both high-level science and outdoor life, Oulu provides an exceptional environment: a compact city with strong infrastructure, short commuting distances, and almost endless possibilities for nature exploration. Read more about Oulu. 

Who are you?

We are looking for a motivated candidate with a strong background in applied mathematics and an interest in computational inverse problems. A Master’s degree in applied mathematics or a closely related field is required. The master's degree should be awarded before the start of the employment contract.

The ideal candidate has strong knowledge of:

• linear algebra
• numerical analysis
• applied mathematics
• scientific computing

A solid understanding of some of the following topics is considered a strong advantage:

• partial differential equations
• inverse problems
• Bayesian methods or uncertainty quantification
• probability theory
• functional analysis
• optimization
• finite element methods
• spectral methods
• numerical methods for PDEs
• computational geometry or manifold-based modelling

Programming experience is expected. Experience with Python, Matlab, Julia, or similar scientific computing languages is beneficial.

The applicant does not need to be an expert in all areas listed above. We especially encourage applications from candidates with a strong mathematical foundation, curiosity, independence, and motivation to develop expertise across theory, computation, and applications.

Salary

The position is fixed-term for 3 years as of 01.09.2026 or as soon as possible thereafter.

The salary will be based on the levels 2-4 of the demand level chart for teaching and research staff of Finnish universities. In addition, a salary component based on personal work performance will be paid (a maximum of 50 % of the job-specific component). The starting gross salary will be approx. 2600-2800 € per month (before taxes).  A trial period of 6 months is applied to the position.

How to apply?

Interested? If yes, please apply by 1.6.2026 (23:59 Finnish local time) through our recruitment system.

The application should be written in English and include the following:

• Cover letter
• CV following the guidelines of the Finnish Advisory Board on Research Integrity
• Certificates/Diplomas
• Contact information of two persons available for recommendation

The eligible applicants fitting best in the profile expected for the position will be invited to an on-site or remote interview. All applicants will be notified during the selection process.

We welcome applicants from all backgrounds, such as people of different ages, genders, and linguistic, cultural, or minority groups. 

Contact Information

For further information, please contact:

Assistant Professor Babak Maboudi Afkham
Research Unit of Mathematical Sciences
University of Oulu
babak.maboudi@oulu.fi