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The University of Jyväskylä (JYU) is seeking a doctoral researcher to join the internationally recognized Multiobjective Optimization Group (https://optgroup.it.jyu.fi/) in the Faculty of Information Technology. The position is part of the multidisciplinary INDENSYS research project, which develops interactive multiobjective optimization methods and tools to support the transition of industrial energy systems toward resilience, carbon neutrality and cost‑effectiveness.
The employment period begins on 1 September 2026 (or other agreed time) and continues until the end of the project 31 December 2029.
As a doctoral researcher, you will contribute to the core scientific work of the INDENSYS project by:
Conducting high‑quality research in multiobjective optimization involving uncertainty modelling, explainability or risk analysis.
Publishing research results in international peer‑reviewed journals.
Completing your doctoral studies as part of the project to get a doctoral degree.
Your research will focus on developing new interactive multiobjective optimization methods to support industrial decision makers navigating complex trade-offs in uncertain, volatile energy markets. You will work at the intersection of mathematical optimization, decision analytics, Bayesian uncertainty modelling, and visual decision support.
Collaboration is central to the position. You will work closely with the international team of researchers at JYU and Aalto University and interact with Finnish industrial partners through real-world case studies. The project provides a rich and inspiring environment for producing scientifically and practically impactful results.
As part of the research project, you will also contribute to the development of open‑source decision-support tools using the DESDEO software framework, implemented in Python. Thus, solid programming skills are important for thriving in this position.
In addition to interactive multiobjective optimization, your doctoral research will target one or more of the following areas:
Approaches allowing experts to express beliefs about uncertain future outcomes (e.g., energy markets, fuel prices), directly influencing optimization results.
Techniques and visualizations that make optimization outcomes understandable and transparent for industrial stakeholders.
Novel methods for incorporating human‑driven risks (e.g., intentional disruptions to critical infrastructure) into energy system decision models.
Strong background in optimization.
Knowledge of multiobjective optimization, decision analytics, uncertainty modelling, or related fields is desirable.
Solid programming and software development skills; Python experience is highly beneficial.
Ability to work independently and in a multidisciplinary team.
Curiosity, motivation, and willingness to tackle complex real‑world problems.
Information for the applicant
The application form cannot be saved as draft. However, after submitting you can return to edit your application via the link you receive by email. The application can be edited until the application deadline.
You have 6 hours to complete your application before the timeout.
The JYU is a nationally and internationally significant research university and an expert on education that focuses on human and natural sciences.
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