KTH Royal Institute of Technology in Stockholm, Sweden, invites applications for up to two PhD positions in machine learning for decision making. The positions are based in the Division of Decision and Control Systems within the School of Electrical Engineering and Computer Science. Successful candidates will join a world-leading research group engaged in interdisciplinary projects focused on developing advanced machine learning models for the regulation and control of complex systems. The division conducts cutting-edge research in areas such as networked control systems, cyber-physical systems, system identification, and transport systems. The research is highly collaborative, involving industrial partners like Hitachi Energy, ABB, Ericsson, and Scania, as well as academic collaborations with top institutions including Caltech, MIT, UC Berkeley, and Stanford. Much of the research is conducted within the Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden's largest individual research program in AI, autonomous systems, and software. Supervision will be provided by Professor Karl Henrik Johansson and Matthieu Barreau, with the final decision made upon admission. The positions offer the opportunity to pursue doctoral studies in a dynamic, international research environment with strong industry and academic connections. Employment is full-time and fixed-term for up to four years, with a monthly salary according to KTH's doctoral student salary agreement. The university provides a supportive environment with a focus on working conditions, equality, diversity, and a vibrant study atmosphere. The location in Stockholm offers proximity to both urban amenities and natural surroundings. Eligibility and Requirements: Applicants must have a master's degree or equivalent (at least 240 ECTS credits, with at least 60 at the advanced level) in a relevant field. Proficiency in English equivalent to English B/6 is required. Selection is based on academic achievements, relevant coursework, and personal qualities such as independence, collaboration skills, and the ability to handle complex problems. Specialization in machine learning, control theory, or mathematics is highly desirable. Application materials must include a CV, cover letter, degree certificates and transcripts, proof of English proficiency, representative publications or technical reports, and contact details for at least three referees. Translations to English or Swedish are required if documents are in other languages. Security clearance may be required for some positions. Application Process: Applications must be submitted via KTH's recruitment system by 2025-11-21. Applicants are responsible for ensuring their application is complete. For more information about the research group and ongoing projects, visit the division's website and WASP . KTH is committed to equality, diversity, and providing a creative and dynamic workplace. The university plays a leading role in education, research, and innovation, contributing to a sustainable society. Join KTH and be part of shaping the future through world-class research and collaboration.

KTH Royal Institute of Technology is seeking up to two doctoral students to join the Division of Decision and Control Systems for research in machine learning for decision making. The project focuses on developing advanced machine learning models to support decision-making in complex systems, with applications in networked control systems, cyber-physical systems, system identification, and transport systems. The division is internationally recognized and collaborates with leading industrial partners such as Hitachi Energy, ABB, Ericsson, and Scania, as well as top academic institutions including Caltech, MIT, UC Berkeley, and Stanford. The research is conducted within the Wallenberg AI, Autonomous Systems and Software Program (WASP), providing a dynamic and interdisciplinary environment. Supervision will be provided by Professor Karl Henrik Johansson and Matthieu Barreau. The position offers a full-time monthly salary according to KTH’s doctoral student salary agreement, along with employee benefits and support for relocation and settling in Stockholm. Applicants must have a relevant master's degree or equivalent, strong background in machine learning, mathematics, and control theory, and proficiency in English. The selection process emphasizes academic excellence, relevant coursework, and personal skills such as independence, collaboration, and analytical ability. The position is for up to four years, with annual or biannual renewal, and may include up to 20% teaching or administrative duties. Applications must be submitted through KTH's recruitment system and include a CV, application letter, diplomas and grades, proof of language proficiency, representative publications or technical reports, and contact information for at least three references. The deadline for applications is November 21, 2025. This is an excellent opportunity to join a leading technical university and contribute to cutting-edge research in machine learning and decision making.

The Division of Decision and Control Systems at KTH Royal Institute of Technology invites applications for up to two doctoral student positions in the area of Learning and Control of Networked Cyber-Physical-Human Systems (CPHS). This research project is situated at the intersection of network dynamics, learning, and control, aiming to address theoretical challenges within networked CPHS. These systems involve humans in interconnected communities making decisions while interacting with cyber-physical or control systems, with applications in complex socio-technical environments such as smart cities. The project will focus on learning complex dynamics from big data, rigorous characterization and data-based modeling of decision-making dynamics over networked CPHS, and the development of novel tools to design and assess the impact of control strategies or interventions. The Division conducts fundamental research in networked control systems and offers opportunities for collaboration with the KTH Live-in Lab and involvement in experimental design. The interdisciplinary nature of the project encourages collaboration with scientists from other fields. Supervision will be provided by Assistant Professor Angela Fontan and Professor Karl Henrik Johansson, both experts in control systems and network theory. The positions are full-time and based in Stockholm, Sweden, with a monthly salary according to KTH's doctoral student salary agreement and a range of employee benefits. The employment is temporary, with a maximum duration corresponding to four years of full-time doctoral education. Doctoral students may also perform certain tasks within their role, such as training and administration, up to 20% of their time. Applicants must meet the admission requirements for postgraduate education, including a second cycle degree (master's or equivalent), or at least 240 higher education credits with 60 at the second-cycle level, and English proficiency equivalent to English B/6. Selection criteria emphasize independence, collaboration, professionalism, and analytical skills, with personal attributes highly valued. Security clearance may be required for some positions. To apply, candidates should submit a CV, application letter outlining their motivation and academic interests, certified copies of diplomas and grades, proof of language requirements, representative publications or technical reports, and contact information for at least three references. Applications must be submitted through KTH's recruitment system by the deadline of March 5, 2026. KTH Royal Institute of Technology is a leading international technical university, committed to advancing education, research, and innovation for a sustainable society. The university offers a creative and dynamic environment, good working conditions, and attractive benefits, with a strong commitment to equality, diversity, and equal opportunities.

The Department of Decision and Control Systems at KTH Royal Institute of Technology invites applications for a postdoctoral position in networked control systems. This research opportunity is ideal for candidates with a strong background in mathematics, modeling, and networked control systems, and offers the chance to contribute to the development of novel mathematical and computational tools for the fundamental understanding and engineering design of emerging networked control systems. The project emphasizes learning and resilient cyber-physical systems, and is supervised by Professors Henrik Sandberg and Karl Henrik Johansson. The department is renowned for its fundamental research in networked control systems, cyber-physical systems, system identification, and transport systems, and maintains strong industrial collaborations with partners such as ABB, Ericsson, and Scania. Research funding is provided by the Swedish Research Council, WASP, Digital Futures, Vinnova, Swedish Energy Agency, and the EU, ensuring a robust and dynamic research environment. The department also boasts an extensive academic network, collaborating with leading institutions including Imperial College, Oxford, ETH, Caltech, MIT, and UC Berkeley. Applicants must hold a doctoral degree or an equivalent foreign degree, with significant, documented research expertise in networked control systems, cyber-physical security, machine learning theory, or applied mathematics. The position is intended as a first career step after dissertation and is offered for up to two years, focusing mainly on research. Preferred qualifications include a doctoral degree obtained within the last three years, teaching abilities, documented supervision of student work, and awareness of diversity and equal opportunity issues, particularly gender equality. Personal skills such as motivation, independence, and collaborative ability are highly valued. To apply, candidates should log into KTH's recruitment system and submit a complete application by the deadline. Required documents include a CV, diplomas and grades, translations if necessary, a brief research statement, three relevant scientific publications, and contact information for at least three references. The position offers a monthly salary and attractive benefits, with good working conditions in a creative and dynamic environment. For further information about the department and research activities, visit www.kth.se/dcs . The application deadline is February 18, 2026. For questions, contact Professors Henrik Sandberg ([email protected]) or Karl Henrik Johansson ([email protected]). Apply online at KTH's recruitment portal .