Doctoral student in Techno-economic Optimization of Thermal Energy Storage KTH Royal Institute of Technology in Sweden

Doctoral position at KTH Royal Institute of Technology in Energy Technology focused on the techno-economic optimization of thermal energy storage (TES) for industrial process heat. The project addresses a major decarbonization challenge: much industrial heat demand is still met with fossil fuels, especially in steam and other medium- to high-temperature applications. TES is explored as a way to integrate renewable heat and electricity, deliver dispatchable process heat, and support the transition to climate-neutral industry.

The research will develop a modular modelling and optimization framework to compare storage concepts under consistent technical, operational, and economic boundaries. Candidate technologies include particle/powder storage, molten salts, and phase-change-material (PCM) systems. The models will consider integration with renewable heat sources such as geothermal and solar thermal energy, along with hybridization through electrification and heat upgrading. The work combines quasi-steady-state modelling, annual optimization, and targeted dynamic modelling when transient effects matter.

The project draws on experimental data, industrial case studies, and collaborations from ongoing projects. Applications include steam supply up to approximately 300 °C and process air up to 400 °C. Expected outcomes include validated modelling tools, harmonized techno-economic indicators, and technology-selection maps identifying cost-effective TES solutions across European industrial and market conditions. Benchmarking against alternative heat-supply options will help formulate practical guidance for technology selection, system design, and investment decisions.

Supervision: Justin Chiu is the main supervisor and Salvatore Guccione is proposed as co-supervisor.

Eligibility: A second-cycle degree (typically a master’s), or equivalent, is required. Applicants must also have completed relevant coursework in thermodynamics, heat transfer, energy system analysis, and optimization methods, together with English proficiency equivalent to English B/6.

Merits: Programming in Python, machine learning, and MILP are advantageous, as are prior skills in thermal energy storage, heat exchangers, and techno-economic modelling. Personal qualities such as independence, collaboration, professionalism, and the ability to manage complex problems are emphasized in selection.

Funding and employment: The position is a full-time doctoral employment for up to four years, with salary according to KTH’s doctoral student salary agreement.

Application: Submit the application via KTH’s recruitment system before the deadline. Required documents include diplomas/transcripts, proof of language requirements, certified translations if applicable, a CV, and a motivation letter of up to two pages.

Deadline: 2026-09-25.