Ragnar Thobaben
Top university
6 days ago
Doctoral student in information and coding theory for federated learning KTH Royal Institute of Technology in Sweden
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Sep 24, 2026
Country
Sweden
University
KTH Royal Institute of Technology

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About this position
Doctoral student in information and coding theory for federated learning at KTH Royal Institute of Technology in Stockholm, Sweden.
This PhD project sits in the third-cycle subject Electrical Engineering and focuses on information- and coding-theoretic methods for improving the resilience and efficiency of federated machine learning. The research targets settings where communication bandwidth is limited and participating nodes may be unreliable, making the project especially relevant to modern distributed learning, communication-efficient machine learning, and robust networked systems.
The position is funded by KTH as part of a joint initiative strengthening collaboration with selected partner universities. The project is carried out in collaboration with the Technical University of Denmark (DTU) in Lyngby, Denmark, and mobility is a requirement. The doctoral student is expected to spend a total of at least one year at DTU, though this period does not need to be continuous and will be planned with the supervisors.
Supervision is shared between KTH and DTU. At KTH, the supervisors are Professor Ragnar Thobaben and Professor Mikael Skoglund. At DTU, the supervisors are Professor Søren Forchhammer and Assistant Professor Stanislav Kruglik. Contact information provided in the announcement includes [email protected].
Eligibility is for applicants with basic postgraduate qualification: either a second-cycle degree such as a master's degree, at least 240 higher education credits including 60 second-cycle credits, or equivalent knowledge. The ideal candidate has a strong background in the theoretical analysis of stochastic phenomena and mathematical analysis of engineered systems. English proficiency equivalent to English B/6 is mandatory. Experience in information theory is considered an advantage, and KTH places strong emphasis on independence, collaboration, professionalism, analytical ability, perseverance, and personal suitability.
The employment is a temporary full-time doctoral position with salary according to KTH’s doctoral student salary agreement. The university notes that admitted doctoral students may be employed for up to four years of full-time doctoral education. Applications must be submitted through KTH’s recruitment system by 2026-09-24.
To apply, candidates should provide diplomas and grade transcripts, documentation of language requirements, a CV, a motivation letter describing research interests and goals, and representative publications or technical reports. KTH asks applicants to ensure the submission is complete and certified where required.
Funding details
Available
What's required
Applicants must have basic eligibility for third-cycle education, demonstrated by a second-cycle degree (for example a master's degree), or at least 240 higher education credits including at least 60 second-cycle credits, or equivalent knowledge. The applicant must have an excellent background in the theoretical analysis of stochastic phenomena and general skills in the mathematical analysis of engineered systems. English proficiency equivalent to English B/6 is mandatory. Prior experience in information theory is a plus, and strong personal skills, independence, collaboration, professional approach, goal orientation, and perseverance are emphasized.
How to apply
Apply through KTH's recruitment system. Submit diplomas and grade transcripts, proof of language requirements, a CV, a motivation/application letter, and representative publications or technical reports. Ensure the application is complete and submitted by the deadline.
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