The research group KU Leuven ESAT-STADIUS is currently offering 2 Postdoc (1 year, extendable) positions within the framework of the ERC (European Research Council) Advanced Grant E-DUALITY http://www.esat.kuleuven.be/stadius/E (PI: Johan Suykens) on Exploring Duality for Future Data-driven Modelling. Within this ERC project E-DUALITY we aim at realizing a powerful and unifying framework (including e.g. kernel methods, support vector machines, deep learning, networks, tensor-based models and others) for handling different system complexity levels, obtaining optimal model representations and designing efficient algorithms. The research positions relate to the following possible topics: -1- Duality principles -2- Multiple data sources and coupling schemes -3- Manifold learning and semi-supervised schemes -4- Optimal prediction schemes -5- Scalability, on-line updating, interpretation and visualization -6- Mathematical foundations -7- Matching model to system characteristics The research group ESAT-STADIUS http://www.esat.kuleuven.be/stadius at the university KU Leuven Belgium provides an excellent research environment being active in the broad area of mathematical engineering, including data-driven modelling, neural networks and machine learning, nonlinear systems and complex networks, optimization, systems and control, signal processing, bioinformatics and biomedicine.
The research will be conducted under the supervision of Prof. Johan Suykens. Interested candidates having a solid mathematical background and PhD degree can online apply by including CV and motivation letter. For further information on these positions you may contact johan . suykens _at_ esat . kuleuven . be.
You can apply for this job no later than September 30, 2021 via the online application tool
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|Titel||Postdoc Positions ERC Advanced Grant E-duality|
|Job location||Oude Markt 13, 3000 Leuven|
|Publicerad||juli 7, 2021|
|Sista ansökningsdatum||september 30, 2021|
|Ämnen||Artificiell intelligens,   Artificiella neurala nätverk,   Kontrollsystemteknik,   Tillämpad matematik,   Beräkningsmatematik,   Maskininlärning,   Signalbehandling  |