Doctoral Researcher in Interactive Multiobjective Optimization Sustainable Industrial Energ

Offer Description

University of Jyväskylä (JYU) is seeking to recruit a Doctoral Researcher to join the internationally recognized Multiobjective Optimization Group in the Faculty of Information Technology. The position is part of the multidisciplinary research project, which develops tools and methods 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 at the end of 2029
.

The research is related to the INDENSYS (Industrial energy systems as part of resilient climate neutral society) project funded by the Research Council of Finland. As a doctoral researcher, you will contribute to the core scientific work of the project by:

• Conducting high‑quality research in multiobjective optimization, uncertainty modelling, explainability, or risk analysis.
• Publishing research results in international peer‑reviewed journals
  .
• Completing your doctoral studies as part of the project.

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 analysis, Bayesian uncertainty modelling, and visual decision support.

Collaboration is central to the position. You will work closely with researchers at JYU, Aalto University, and the project’s international collaborators and interact with Finnish industrial partners through real‑world case studies. The project provides a rich 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 open‑source software framework DESDEO
, implemented in Python
. Thus, solid programming skills are important for thriving in this position.

• Interactive visualizations for multiobjective optimization – Visualizations that help decision makers explore the solutions and objective function values in detail (e.g., visualizations for showing uncertainty in objective functions or diagrams showcasing interdependencies or technical details).
• Uncertainty modelling and Bayesian belief elicitation in interactive multiobjective optimization – 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 and trade‑offs understandable and transparent for industrial stakeholders.
• Adversarial and probabilistic risk analysis – Novel methods for incorporating human‑driven risks (e.g., intentional disruptions to critical infrastructure) into energy system decision/optimization models.

• Strong interest in multiobjective optimization, decision analytics, uncertainty modelling, or related fields.
• Solid programming and software development skills;
  Python experience is highly beneficial.
• Ability to work independently and collaborate in a multidisciplinary team.
• Curiosity, motivation, and willingness to tackle complex real‑world problems.

Applicants must have:

• A master’s degree in a relevant field (e.g., computer science, mathematics, applied mathematics, operations research, industrial engineering, or a closely related discipline).
• Good written and spoken English skills for research communication, publication, and collaboration.
• Knowledge of Finnish is not required but considered beneficial for interaction with Finnish industry partners.

The selected candidate must obtain doctoral study rights through a separate application procedure from the Faculty of IT (with the help from the supervisors) before the start of employment. Therefore, corresponding eligibility requirements must be met. A trial period of six months will be used in the beginning of the employment.

• A stimulating research environment in a globally recognized research group.
• Supervision by leading experts in…