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Join us in an interdisciplinary research project at the intersection of Computational Fluid Dynamics (CFD) and Artificial Intelligence (AI) for future flexible hydropower operation.

Your work assignments

As a PhD student, you will conduct research at the intersection of Computational Fluid Dynamics (CFD), fluid mechanics, and Artificial Intelligence (AI), with a particular focus on developing deep reinforcement learning methods for active flow control of hydraulic turbine instabilities. The project aims to develop novel AI-based control strategies that enable safer and more flexible operation of hydropower systems under changing operating conditions.

Your work will involve developing and applying high-fidelity CFD models of turbulent flows in hydraulic turbines, integrating machine learning and deep reinforcement learning algorithms with numerical simulations, and investigating how intelligent control can mitigate harmful flow instabilities compared with conventional open-loop control strategies. Particular emphasis will be placed on swirling draft tube flows and vortex-induced instabilities in hydraulic turbines, building on previous research within the group. You will design and perform large-scale numerical experiments, analyze complex flow phenomena using advanced data analysis techniques, and contribute to the development of new computational tools and methodologies.

The research combines fundamental fluid mechanics with modern AI methods and includes both methodological development and application to realistic engineering systems. The results are expected to contribute to future renewable energy systems by improving the reliability, efficiency, and operational flexibility of hydropower.

You will work in a collaborative research environment and publish your findings in leading international journals and conferences.

More information about the research project is available at: https://saeedsalehi.com/project-hydropower-ai.html

As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time.

Your qualifications

You have graduated at Master’s level in Mechanical Engineering, Engineering Physics, Energy Engineering, Applied Mathematics, or a related field, or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses within the above-mentioned areas. Alternatively, you have gained essentially corresponding knowledge in another way.  The requirement for a degree must be met no later than the time the employment decision is finalized, which occurs when the employment contract is signed.

The position requires a strong background in fluid mechanics and computational fluid dynamics (CFD), as well as good programming skills. Excellent written and oral communication skills in English are required.

As a person, you are analytical, self-motivated, and able to work both independently and collaboratively. You have a strong interest in scientific research and a willingness to work at the intersection of fluid mechanics, numerical simulation, artificial intelligence, and hydropower applications.

It is particularly meritorious to have experience in several of the following areas:

• Open source CFD, such as OpenFOAM
• Machine learning, deep learning, or reinforcement learning
• Scientific programming in Python and/or C++
• High-performance computing (HPC) environments
• Turbulence modelling and numerical methods
• Control theory and flow control
• Linux, version control (e.g., Git), and LaTeX

Excellent academic results are also considered a strong merit.

The application should include a brief statement of interest (maximum two pages) describing your background, research interests, and motivation for applying for this position.

Your workplace

You will be employed at the Division of Applied Thermodynamics and Fluid Mechanics, Department of Management and Engineering (IEI), Linköping University. The division conducts research and education in fluid mechanics, heat transfer, aerodynamics, biological flows, and thermodynamics, with an emphasis on computational methods and engineering applications.

The PhD project is funded by the ÅForsk Foundation and will be conducted as a close collaboration between the Division of Applied Thermodynamics and Fluid Mechanics at Linköping University (principal supervisor Saeed Salehi) and the Division of Fluid Dynamics at Chalmers University of Technology (co-supervisor Håkan Nilsson).

The project also includes collaboration with industrial partners in the Swedish hydropower sector, providing opportunities to connect fundamental research with real engineering challenges and future industrial applications.

The employment

When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University

The employment has a duration of four years’ full-time equivalent. You will initially be employed for a period of one year. The employment will subsequently be renewed for periods of maximum duration two years, depending on your progress through the study plan. The employment may be extended up to a maximum of five years, based on the amount of teaching and departmental duties you have carried out. Further extensions can be granted in special circumstances.

Starting date by agreement.

Salary and employment benefits

The salary of PhD students is determined according to a locally negotiated salary progression.

More information about employment benefits at Linköping University is available here.

Union representatives

Information about union representatives, see Help for applicants.

Application procedure

Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than August 31, 2026.

Applications and documents received after the date above will not be considered.