Postdoc in Machine Learning, Autonomous Decision-Making, and Optimization

The Division of Decision and Control Systems at KTH Royal Institute of Technology invites applications for two postdoctoral positions in machine learning, autonomous decision-making, and optimization. The research group is renowned for its fundamental work at the intersection of machine learning, optimization, and decision-making, with a strong emphasis on next-generation networked systems. As a postdoc, you will have the opportunity to shape your research agenda within a broad and dynamic scope, choosing between two main tracks: Fundamental Algorithms & Theory, which focuses on developing rigorous mathematical frameworks for distributed optimization, learning, and decision-making under uncertainty, and Distributed Intelligence for 6G, which centers on designing algorithmic foundations for 6G wireless networks, including distributed and federated learning over wireless edges. The group is well-funded through major grants such as WASP, KAW, and VR, and maintains an extensive international network. The research environment is vibrant, aiming for publications in top-tier venues like NeurIPS, ICML, AISTATS, IEEE Transactions, and leading control and signal processing conferences. The position is intended as a stepping stone toward a future tenure-track academic career. You will be supervised by Professor Mikael Johansson and collaborate closely with PhD students and senior researchers. The role may include limited teaching or supervision duties (up to 20%), allowing you to focus primarily on research. Applicants must hold a doctoral degree (or equivalent foreign degree) in electrical engineering, computer science, or applied mathematics, completed by the time of employment. Essential qualifications include a strong mathematical background in optimization, linear algebra, and probability, documented research expertise in machine learning, control theory, or applied mathematics, and excellent English communication skills. Preferred qualifications are a recent doctoral degree (within three years), experience with distributed optimization, decentralized and federated learning, programming skills (Python, C/C++, Matlab), and awareness of diversity and equal opportunity issues. Prior knowledge of wireless communications is not strictly required for candidates focusing on the theoretical track, provided they have strong methodological skills. Personal attributes such as scientific curiosity, independence, and collaborative ability are highly valued. KTH offers a creative and dynamic environment with good working conditions, attractive benefits, and a commitment to equality, diversity, and equal opportunities. The position is full-time, temporary (up to two years), and based in Stockholm, Sweden. The application deadline is March 27, 2026. To apply, submit your CV, diplomas and grades, translations if necessary, and a brief research statement via the KTH recruitment system. For further information, contact Professor Mikael Johansson at [email protected].