Postdoctoral positions in Distributed Learning and Optimization

The Department of Electrical Engineering at Uppsala University conducts successful research and education in the areas of control and signal processing, machine learning, industrial IoT, 6G communication and wireless sensor networks as well as research and education within renewable energy, electric vehicles, Life Sciences, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with around 170 employees that all contribute to important technical energy and health challenges at the Ångström Laboratory.

We are pleased to announce up to two post-doctoral positions, which will be based in the division of Signals and Systems, at the Department of Electrical Engineering.

Project description: Distributed machine learning enables cross-device collaborative learning without exchanging raw data, ensuring privacy and reducing communication cost. In applications such as networked autonomous systems, mobile robotics etc., learning over wireless networks poses significant challenges due to limited communication bandwidth and channel variability, limited computational resources at the IoT devices, the heterogeneous nature of distributed data, and also randomly time-varying network topologies. In this project, the aim is to design and analyze fast, low-complexity communication-efficient distributed learning and optimization algorithms that are adaptive to the constraints posed by the underlying wireless networks. Furthermore, in distributed settings, malicious nodes can disrupt the training process through transmitting false data and byzantine attacks. Designing byzantine resilient distributed machine learning algorithms under privacy constraints is also a challenging task, that will be investigated in this project. The nature of this project is multi-disciplinary, requiring tools from distributed optimization and control, wireless communications and networks, signal processing, statistical machine learning, random matrix theory and privacy and security tools. This project will advance the state-of-the-art in robust distributed learning over wireless networks, and also contribute to design guidelines for practical learning algorithms.

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Duties: The main duties of these positions include

• Conducting theoretical and applied research in the field of distributed optimization and machine learning, in particular, to develop novel Federated and fully distributed machine learning/optimization algorithms, to carry out performance analysis of these algorithms on synthetic and real datasets, and to design byzantine resilient privacy preserving distributed learning algorithms
• Writing high quality technical research papers suitable for publication in highly regarded journals such as the IEEE Transactions, Automatica,Journal of Machine Learning Research, and also in top-tier international conferences in the area
• Taking part in research dissemination through departmental seminars, conference presentations nationally and internationally
• Teaching of undergraduate/postgraduate course amounting to no more than 20% of full-time workload

Requirements

• The applicant must hold a PhD degree or a foreign degree equivalent to a PhD degree in Electrical or Computer Engineering/Applied Mathematics with specialization in control and optimization, or statistical machine learning.
• The degree needs to be obtained by the time of the decision of employment. The degree needs to be obtained by the time of the decision of employment. Priority will be given to applicants who have completed their degree no more than three years before the deadline for applications. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.
• Strong analytical and mathematical skills, and good working knowledge of several of the following topics: control theory, convex optimization, statistical machine learning, signal processing and wireless communications, differential privacy and homomorphic encryption
• Good programming skills in MATLAB or Python (essential) and C++ (desirable)
• Very good oral and written proficiency in English.
• Ability to carry out independent research as well as effectively collaborate with other team members.

About the employment
The employment is a temporary position of 2 years according to central collective agreement. Full time position. Starting date 2026-06-01 or as agreed. Placement: Uppsala

For further information about the positions. please contact Professor Subhrakanti Dey (subhrakanti.dey@angstrom.uu.se). Information about the division of Signals and Systems can be found at www.uu.se/en/department/electrical-engineering.

Your application must include:

• A cover letter including a motivation of why you are interested in this position and how the position aligns with your qualifications, as well as a short description of your previous research experience,
• your CV,
• your list of publications,
• other relevant documents, such as names of 2-3 referees

Please submit your application by February 23, 2026, UFV-PA 2026/304.

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