WASP Postdoctoral Position in Autonomous Optimization - Hiring in process/Finished, not possible to apply
KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program, and provides a platform for academic research and education, fostering interaction with Sweden’s leading companies. The program addresses research in artificial intelligence, autonomous systems and software as enabling technologies for development of systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems of systems. The program is conducted in close cooperation between leading Swedish universities with an aim to promote the competence of Sweden as a nation within the area of AI, autonomous systems and software.
Autonomous Optimization is one out of seven WASP Expedition Projects (high gain/high risk targeted projects with a specific challenging goal). The research a will focus on development of autonomous optimization, i.e. how to use tools from machine learning to automatically design and tune optimization algorithms. In particular, we plan to investigate how learn new efficient distributed optimization methods suitable for decision-making in autonomous systems and AI/ML. The main research challenges of the project are in the intersection between optimization, control and machine learning. This is a collaborative project between the Optimization Group headed by Professor Anders Hansson within the Division of Automatic Control at the Department of Electrical Engineering at Linköping University and the Department of Automatic Control headed by Professor Bo Wahlberg at KTH Royal Institute of Technology, Stockholm, Sweden. The Department of Automatic Control at KTH Royal Institute of Technology conducts research, education and industry/society interplay within modelling, identification, control, learning and optimization of dynamical systems. It consists of ten faculty, 20 postdocs and over 50 PhD students.
We are offering one two-year postdoctoral position at the Department of Automatic Control, School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology, Stockholm, Sweden. Successful candidate will be able to join the WASP research network with over 150 active PhD students and researchers.
A doctoral degree (or close to completion) in Systems and Control, Signal Processing , Machine Learning , Applied Mathematics, or related field is required. The doctoral degree must have been obtained within the last three years from the application deadline (some exceptions for special grounds, for instance sick leave and parental leave) Ideal candidates must have a strong background in Systems Theory, Automatic Control, Optimization and Statistical Learning. Excellent interpersonal, written, and oral communication skills and ability to write peer reviewed papers. An candidate must have the ability to collaborate with a multidisciplinary team of scientists and industry. Experience of developing efficient computer code is required.
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The application should contain the following:
- CV including relevant professional experience and knowledge.
- Copies of diplomas and grades from your previous university studies. Translations to English or Swedish if the original documents are not issued in one of these languages.
- Brief explanation of why you want to conduct research, about your academic interests and how they relate to your previous studies and future goals; max 2 pages long.
- Representative publications or technical reports: Document no more than 10 pages each. For longer documents (eg dissertations), attach a summary (abstract) and a web link to the full text.
- Recommendation letters
- Contact information for two reference persons. We reserve the right to contact references only for selected candidates.
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|Type of employment||Temporary position longer than 6 months|
|Contract type||Full time|
|First day of employment||According to agreement|
|Number of positions||1|
|Working hours||100 %|
|Last application date||18.Feb.2019 11:59 PM CET|