György Dán

KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for a doctoral student position in AI-native Edge Computing for 6G. This research project is situated within the third-cycle subject of computer science and aims to design next-generation edge computing systems that are deeply integrated with future 6G wireless networks. The project will address the challenges of delivering massive improvements in speed, responsiveness, and energy efficiency by developing smart, distributed computing architectures built directly into the network infrastructure. Research will focus on combining heterogeneous computing platforms with distributed MIMO architectures to support both real-time AI workloads and traditional signal processing. The overarching goal is to create intelligent, scalable, and sustainable network nodes capable of handling a wide range of tasks, from user services to advanced coordination. A significant emphasis will be placed on the development of optimization algorithms that incorporate machine learning components, with opportunities for collaboration with industrial partners such as Ericsson, Atlas Copco, and Telenor, as well as the TECoSA competence center at KTH. The Division of Network and Systems Engineering at KTH conducts fundamental research in networked systems, wireless communications, and cyber security. The research environment is highly collaborative, with connections to leading academic institutions including MIT, UIUC, and EPFL. The position is part of major research initiatives such as the Wallenberg AI, Autonomous Systems and Software Program and Digital Futures, providing a vibrant and innovative setting for doctoral studies. Supervision will be provided by Professors György Dán, Emil Björnson, and Cicek Cavdar, offering expertise in networked systems, wireless communications, and optimization. The position is full-time, temporary, and funded with a monthly salary according to KTH's doctoral student salary agreement, including employee benefits. The employment period is up to four years, with possible renewals as per KTH regulations. Eligibility requirements include a second cycle degree (e.g., master's) or equivalent, with at least 240 higher education credits (60 at the second-cycle level), and English proficiency equivalent to English B/6. Selection criteria emphasize academic excellence, relevant coursework, personal skills, and specialization in optimization, mathematical statistics, or machine learning. Applicants should be goal-oriented, able to work independently and collaboratively, and possess strong analytical abilities. Applications must be submitted via KTH's recruitment system by January 11, 2026. Required documents include a CV, diplomas, grades, language certificates, certified translations if applicable, and representative publications or technical reports. KTH is committed to equality, diversity, and providing a creative and dynamic environment for growth and development. For further information, contact Professor György Dán at [email protected]. Join KTH and contribute to shaping the future of wireless infrastructure and AI-driven edge computing in a leading international technical university.

This doctoral position at KTH Royal Institute of Technology focuses on advancing battery energy storage participation in the Nordic electricity market, supporting the transition to a sustainable, low-carbon energy system. As renewable generation increases, battery storage is crucial for providing flexibility, ensuring system reliability, and improving market efficiency. The project tackles three main challenges: designing market-compatible bidding structures for battery storage that reflect operational constraints, developing tailored financial hedge contracts to manage revenue risks in low-volatility markets, and enabling co-optimization of energy and reserve services using advanced optimization and AI-assisted methods. The research combines mathematical modeling, electricity market design, and computational optimization, offering the doctoral student opportunities to contribute to both theoretical developments and real-world applications. Collaboration with leading industry partners such as Nord Pool and Fortum is integral to the project, providing valuable industry exposure and practical relevance. Supervision will be provided by Prof. Mohammad Reza Hesamzadeh and Prof. György Dán (KTH), Prof. Derek Bunn (London Business School), and Prof. Darryl Biggar (Monash University), ensuring a diverse and international academic environment. The position is based in Stockholm, Sweden, at KTH Royal Institute of Technology, a leading technical university renowned for its research and innovation in sustainable energy systems. Applicants must hold a Master’s degree in Electrical Engineering, Energy Systems, Engineering Physics, Applied Mathematics, Operations Research, or a closely related field. Essential skills include a strong background in mathematical optimization (linear, mixed-integer, or nonconvex), understanding of energy systems and electricity markets, computer programming, and analytical problem-solving. Candidates with backgrounds in mathematics, physics, or computer science and a strong interest in energy systems are encouraged to apply. English proficiency equivalent to English B/6 is mandatory. Selection criteria emphasize the ability to work independently, collaborate effectively, maintain a professional approach, and analyze complex issues. Experience with stochastic optimization, decomposition methods, large-scale optimization, electricity market design, ancillary services, or flexibility markets is considered advantageous. The position offers full-time employment for up to four years, with a monthly salary according to KTH’s Doctoral student salary agreement and access to employee benefits. To apply, candidates must submit certified copies of diplomas and grades, proof of language requirements, CV, application letter (maximum 2 pages), and representative publications or technical reports. Applications should be submitted via KTH’s recruitment system by the deadline of June 6, 2026. For further information, contact Prof. Mohammad Reza Hesamzadeh ([email protected]) or Prof. György Dán ([email protected]). KTH offers a creative and dynamic environment with good working conditions and attractive benefits. Equality, diversity, and equal opportunities are central to KTH’s values. Join KTH to contribute to cutting-edge research and innovation in sustainable energy systems.