Embedded optimization
Created Wednesday 06 November 2013
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TEMPO: Training in Embedded Predictive Control and Optimization
Contact: Prof. Colin Jones (colin.jones@epfl.ch)
Embedded optimization methods offer the most powerful technology to automate real-time decisions with little or no human intervention. TEMPO will bring the advantages of these proven control techniques to a vastly increased range of applications by developing novel optimization-based control theory and software methodologies targeted specifically at high-speed, low-cost embedded systems.
The student will work in a collaborative project involving 10 leading European universities and companies and will join a team with a wide expertise in control, optimization and computational methods. A candidate successfully completing a PhD within this team can expect to become an expert in optimization, predictive control and the practical application of these techniques in a challenging domain. The project involves a solid mix between control and optimization theory and the development of practical optimization-based control tools: the candidate will be expected to develop novel theory in the area of real-time embedded predictive control, and to develop and prove their techniques via open community software.
The ideal candidate will have a background in control systems and / or optimization, solid programming skills and an interest in developing both novel theory, as well as practical tools. Outstanding students with only a partial match to this list are encouraged to apply.