Machine learning, nonlinear system identification, feedback control, stochastic optimization
Development of novel stochastic gradient descent methods for learning nonlinear optimal feedback policies from input/output data collected from a dynamical system, such as policies defined by neural network structures.
IMT Lucca invites applications from candidates with expertise in machine learning and feedback control design, preferably with an undergraduate background in mathematics or engineering, and with programming skills in Python and MATLAB.
- Master Degree in Mathematical Engineering or fields related to the subject of this call
- Excellent knowledge of English, both written and spoken.
Apply ONLINE only.
- Personal info and contact info (compulsory);
- University degree (compulsory).
- The scanned copy of a valid identity document (Passport or Identity Card - compulsory);
- Your CV in English (compulsory).