Postdoc in Learning-Based Multi-Agent Control under Uncertainty

The Technical Faculty of IT and Design, Department of Electronic Systems, Automation and Control, Aa; Aalborg; On-site; DKK 360,000 - 480,000; Full time

Job summary

Aalborg University invites applications for a postdoc in learning-based multi-agent control under uncertainty, with applications to autonomous multi-robot systems in dynamic environments. The position is funded for two years and starts as soon as possible, potentially February 1, 2027.

The research focuses on distributed and cooperative control, safety, robustness, and performance, combining learning with model-based methods.

Qualifications

• PhD required in control engineering, robotics, electrical engineering, applied mathematics, computer science, or closely related field.

Responsibilities

• Conduct fundamental research on learning-based planning and control of interacting autonomous agents under uncertainty.

Skills

Mathematical modelling

Control theory

Optimization

Multi-agent systems

Scientific programming

Python

MATLAB

C++

ROS/ROS 2

Robotics

Education

PhD in a relevant field

Tools

Python

MATLAB

C++

ROS/ROS 2

Simulation software

Job description

Postdoc in Learning-Based Multi-Agent Control under Uncertainty

The Technical Faculty of IT and Design, Department of Electronic Systems, Automation and Control, Aalborg

The Department of Electronic Systems at the Technical Faculty of IT and Design invites applications for a postdoc in learning-based multi-agent control under uncertainty, with applications to autonomous multi-robot systems operating in dynamic and uncertain environments, as per February 1, 2027 or as soon as possible thereafter. The position is available for a period of 2 years.

Your work tasks

The position focuses on fundamental research in learning-based planning and control of interacting autonomous agents under uncertainty. You will develop new theoretical and algorithmic approaches for distributed and cooperative control, combining learning or online adaptation with principled treatment of safety, robustness, and performance. Research challenges include uncertain dynamics and disturbances, partial or noisy information, changing interactions between agents, and limited or unreliable communication.

A central part of the work will be to formulate rigorous methods and establish their properties, for example concerning stability, safety, constraint satisfaction, robustness, and convergence, where applicable. Depending on the research direction, the work may draw on learning-augmented model predictive control, safe reinforcement learning, data-driven modelling and safety mechanism (e.g. CBF), distributed optimization, or robust and adaptive control. You will develop reproducible numerical studies and simulations to examine the strengths, limitations, and scalability of the proposed methods.

The research will be carried out in the Horizon Europe ROX-6G project, where heterogeneous robot teams provide a compelling application for coordination under uncertain conditions and connectivity constraints. Although the position is primarily theoretical, you will collaborate with colleagues working on robotic implementation and will contribute to experimental validation. You will lead and co-author publications in international journals and conferences, engage with project partners, contribute to research planning and scientific discussions, and support knowledge exchange within the team.

Your competencies

We seek a researcher with a PhD in control engineering, robotics, electrical engineering, applied mathematics, computer science, or a closely related field, and a strong background in mathematical modelling, control, optimization, or multi-agent systems.

You should be able to formulate original research problems, develop and analyse rigorous methods, and demonstrate research quality through peer-reviewed scientific publications. Experience in learning-based control, robust or nonlinear control, distributed control, or decision-making under uncertainty is particularly relevant; expertise in every one of these areas is not expected.

You should have good scientific programming skills, for example in Python, MATLAB, or C++, and be able to evaluate algorithms systematically through simulation. We value independent research initiative, clear scientific writing, and the ability to work constructively with researchers from different disciplines and backgrounds. Experience with autonomous robots, ROS/ROS 2, multi-robot simulation, or physical robotic experiments will be considered an advantage, but is not a prerequisite for this primarily theory-oriented position. Excellent written and spoken English is required.

Who we are

In electronic engineering, Aalborg University is known worldwide for its high academic quality and societal impact. The Department of Electronic Systems employs more than 200 people, of which about 90 are PhD students, and about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control systems, AI, sound, cyber security, and robotics. The department plays an active role in transferring inventions and results into applications in close collaboration with industrial partners worldwide. You can read more about the department at www.es.aau.dk.

The position is hosted in the Automation and Control Section, within a collaborative robotics research environment combining fundamental research with real-world applications.

In addition, you will work with an international team and research partners in ROX-6G, a European collaboration addressing autonomous robotic operations in demanding underground environments. Our research interests span safe and resilient decision-making, learning-enabled control, distributed multi-robot coordination, and validation in simulation and on robotic platforms. We encourage scientific independence, close exchange of ideas, and publication of high-quality research. More information: www.es.aau.dk.

Qualification requirements

Appointmentaspostdoc requires academic qualifications at PhD level.

Do you have any questions?

If you have any questions about the position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost.

Further information

Read more about our recruitment process here

The appointment process at Aalborg University involves a shortlisting process. You can read more about the shortlisting and appointment process here .

The hiring process at Aalborg University may include a risk assessment as a tool to identify potential risks associated with new hires, ensuring the safety, compliance, and integrity of the workplace.

Salary and terms of employment

The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities and the Ministerial Order on Job Structure for Academic Staff at Universities. Furthermore, your terms of employment and salary are in accordance with the collective agreement between the Danish Confederation of Professional Associations and the state (AC collective agreement) and protocol on certain terms of employment of academic staff at universities.

Aalborg University - Knowledge for the world
Aalborg University is an international workplace with more than 3,700 employees. We offer real-world-oriented education and create world-class research results through collaboration between researchers, students, and public and private companies. This is how we achieve insights, new solutions to societal problems, and knowledge that changes the world. Our main campus is in Aalborg, but we also have campuses in Esbjerg and Copenhagen.

Type of employment

Type of employment Temporary position more than 6 months

Contract type

Contract type Full time

Number of positions

Number of positions 1

Full-time equivalent 37

City

City Aalborg

County *

Country

Reference number

Reference number 2026/1221

Contact