PhD position in Collaborative Autonomous Multi-Agent Systems

Electrification and digitalisation are among the largest areas for the future in the conversion to sustainable societies. The Department of Electrical Engineering conducts successful research and education in the areas - renewable energy sources, electric vehicles, industrial IoT, 6G communication and wireless sensor networks as well as research and education within Life Science, smart electronic sensors and medical systems. The Department of Electrical Engineering is an international workplace with around 160 employees that all contribute to important technical energy and health solutions at the Ångström Laboratory.

Join us and build the future with us!
The position will be at the Division of Signals and Systems, at the Department of Electrical Engineering. Here you will find a friendly work environment and exciting research projects. The Division of Signals and Systems collaborates with Swedish companies - public and private - and stakeholders in the different fields of research. We look forward to receiving your application. 

Project description
Autonomous systems are intelligent agents—such as robots, vehicles, or drones—that can sense their environment, make decisions, and act independently. When multiple such agents work together, cooperative autonomous systems emerge. These systems hold transformative potential in applications like robotics, environmental monitoring, smart transportation, warehouse automation, and disaster response.

Through cooperation and coordination, autonomous agents can accomplish tasks that are too complex, unsafe, or large-scale for a single agent to handle alone. This research area lies in the intersection of control theory, robotics, artificial intelligence, and signal processing, and is a key enabler of future intelligent infrastructure.

This project will focus on the development of novel control, coordination, and decision-making algorithms for multiple autonomous agents—such as robots (robotic manipulators, drones, or vehicles)—that work together to achieve common goals in dynamic, uncertain environments.

We have an exciting work environment designed by the doctoral student and the research team together. The doctoral student will be supervised by at least two supervisors. The Department of Electrical Engineering also gives a salary supplement for the doctoral students employed at the Department of Electrical Engineering.

Duties
The PhD student will carry out research in the area of cooperative autonomous systems. The successful candidate will explore topics such as:

• Multi-agent reinforcement learning 
• Distributed control and estimation
• Multi-agent planning and cooperation
• Communication-aware coordination strategies
• Learning-based control in networked systems
• Resilience and safety in multi-agent systems
• Applications in robotics, autonomous driving, healthcare, smart mobility and sensor networks

The PhD student will actively contribute to setting up the research questions in their doctoral project.  They will take an active role in planning, implementing and, where necessary, modifying their research project. The PhD student will gain advanced and up-to-date specialized knowledge in the area. They will develop new theory and methods; and analyze the generalization performance of these methods. The work as a doctoral student also includes writing scientific publications and presenting research results orally in various contexts such as project group meetings as well and international conferences.

The main task of a doctoral student is to devote to the doctoral education, which includes both participation in research projects and doctoral education courses. The duties also include participating in teaching and other institutional tasks to a maximum of 20% of the working time.

Requirements

To meet the general entry requirements for doctoral studies, you must:

• hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, machine learning, data science, computer science, applied mathematics or in a similar field, or
• have completed at least 240 credits in higher education in these fields, with at least 60 credits at Master’s level including an independent project worth at least 15 credits, or
• have acquired substantially equivalent knowledge in some other way.

We are looking for candidates with:

• a strong interest in developing new theory and methods for autonomous systems
• strong mathematical background
• good proficiency in programming (Python, MATLAB, or C++)
• good oral and written proficiency in English
• a structured, self-driven, independent approach to technical work and good collaboration skills 

Additional qualifications
Coursework or other experiences with the following subjects are valued: automatic control, reinforcement learning, optimization, linear algebra, signal processing, probability, random processes, statistical machine learning, deep learning. 

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

Application: Please use the link below. The application must contain:

• A cover letter (max 1 page), in English. The cover letter should include a self-assessment on why you would be the right candidate for this position
• A curriculum vitae (CV).
• A copy of diplomas, certificates and transcripts (translated into Swedish or English).
• The Master’s thesis (or a draft, and/or some other self-produced technical or scientific text), publications, and other relevant documents.
• Contact information for two references (names, emails and telephone number). 

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date as agreed. Placement: Uppsala 

For further information about the position, please contact: Christos Verginis (christos.verginis@angstrom.uu.se), Ayca Ozcelikkale, (ayca.ozcelikkale@angstrom.uu.se), Roland Hostettler (roland.hostettler@angstrom.uu.se)

Please submit your application by May 30th, 2025, UFV-PA  2025/1448.

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