The doctoral student will contribute to energy system optimization research, developing AI-driven forecasting algorithms, designing optimization models for multi-energy investment planning, and conducting data analytics for large-scale energy datasets. The research includes developing Long-Term Strategy (LTS) tools for PED planning and techno-economic assessment of energy community solutions. The PhD candidate will engage in international cooperation with EU partners across Italy, Portugal, Greece, Belgium, and Sweden, while contributing to validation activities at the Tamarinden Energy Community in Örebro.
Supervision: Dr. Jagruti Thakur and Prof. Björn Laumert are proposed to supervise the doctoral student. Decisions are made on admission
What we offer
- The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities from all over the world.
- A workplace with many employee benefits and monthly salary according to KTH’s Doctoral student salary agreement.
- A postgraduate education at an institution that is active and supportive in matters pertaining to working conditions, gender equality and diversity as well as study environment.
- Work and study in Stockholm, close to nature and the water.
- Guidance on relocating and settling in at KTH and in Sweden
Admission requirements
To be admitted to postgraduate education (Chapter 7, 39
- Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:
- passed a second cycle degree (for example a master’s degree), or
- completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
- acquired, in some other way within or outside the country, substantially equivalent knowledge
Completed coursework or course modules in energy systems and optimization methods is required in accordance with admission criteria for the specified third cycle studies. Specific knowledge in machine learning, data analytics, sector-coupling and Mixed-Integer Linear Programming (MILP) is a merit.
Summary:
| Employment form | Fixed-term employment |
|---|---|
| Scope of employment | Full-time |
| Access | By agreement |
| Salary form | Monthly salary according to KTH’s agreement for doctoral student salaries |
| Number of vacant positions | 1 |
| Employment rate | 100% |
| City | Stockholm |
| County | Stockholm County |
| Country | Sweden |
| Reference number | PA-2025-2528 |
| Contact | Jagruti Ramsing Thakur, jrthakur@kth.se |
| Published | 2025-09-04 |
| Application deadline | 2025-10-01 |
About the Author
