Signal Processing Group
Department of Signal Theory & Communications Universidad Carlos III de Madrid (Spain)
The Signal Processing Group (SPG) of Universidad Carlos III opens one post-doctoral position to carry out research in sequential Monte Carlo methodologies for tracking of high dimensional dynamical systems. This includes classical multi-target tracking applications as well as the forecasting of destructive meteorological phenomena.
SPG is a dynamic team conducting both fundamental and applied research in the fields of machine learning, Monte Carlo statistical methods and information theory, with financial support both from public administrations (Spanish and European) and the industry. The Department of Signal Theory & Communications is integrated into the Polytechnic School of Universidad Carlos III, where several Engineering degrees are imparted, and located in Leganés, a lively town 15 kms away from the center of Madrid and well communicated by public transport (train, subway and bus).
The offer:
We invite applications to cover one postdoc position. The tasks of the successful candidate will involve the analysis, design and evaluation of sequential Monte Carlo algorithms, as well as collaboration in the development of demonstrators. Working languages are English and Spanish.
We offer a 1-year contract, which can be extended for up to two additional years. The minimum salary is 21,924 euros/year, but this can be negotiated, depending on the candidate qualifications
This position will be funded by the Office of Naval Research (ONR) Global.
Deadline:
This call will remain open until the position is filled. Therefore, there is no strict deadline and the appointment can be made at any time. However, we aim at incorporating a successful candidate on October 1, 2015, or as soon as possible thereafter.
How to apply:
Potential candidates are encouraged to contact:
Dr. Joaquin Miguez,
Associate Professor
Department of Signal Theory and Communications
Universidad Carlos III de Madrid
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www.tsc.uc3m.es/~jmiguez
tlf: +34 91 624 8736
Please, send a recent CV with details about education background, research interests and publications.
