Author Archives: Václav Vodička

Modeling pathological gait resulting from motor impairments: compare and combine neuromechanical simulation and machine learning approaches

Within this project we seek to develop machine learning methods for the modelling of pathological human locomotion. This is a collaborative Sinergia project funded by the Swiss National Science Foundation. Continue reading

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OrbiLoc: Learning to position IoT devices in outdoor environments

Location-based services are expanding at an ever increasing speed. They address individual consumer demands as well as the needs of industrial and service organizations active in the private or the public sector. To deliver their expected value location-based services require adapted sensing and network technologies, in particular for large areas. Within this project we will develop machine learning and neural networks to ascertain sensor location. Continue reading

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Learning olfactory models to support the perfume creation process

We will develop a data-driven methodology which will allow us to uncover the olfactory perception mechanisms related to perfume creation and exploit them to build rational solutions that improve product performance and differentiation. We will do so by designing and … Continue reading

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RAWFIE (Road-, Air-, and Water- based Future Internet Experimentation)

RAWFIE (Road-, Air-, and Water- based Future Internet Experimentation) is a project funded by the European Commission (Horizon H2020 programme) under the Future Internet Research Experimentation (FIRE+) initiative that aims at providing research facilities for Internet of Things (IoT) devices.

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PhD position on learning and simulation for human locomotion modelling (open)

We have an opening for a PhD position on the development of machine learning methods for the modelling of pathological human locomotion in the framework of a collaborative Sinergia project funded by the Swiss National Science Foundation. The goal of the project is to develop, through machine learning and neuromechanical simulation, accurate models of human locomotion, together with Stephane Armand (University of Geneva, Kinesiology laboratory) and Auke Ijspeert (Biorobotics laboratory, EPFL, BIOROB). The project will (1) model pathological gaits resulting from motor impairments such as cerebral palsy, and (2) compare and combine neuromechanical simulation and machine learning approaches for gait analysis. It brings together expertise on pathological gait, neuromechanical simulation models, machine learning, coupled with a unique collection of relevant real world data. Continue reading

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PostDoc position on learning and simulation for human locomotion modelling (closed)

We have an opening for a PostDoc position on the development of machine learning methods for the modelling of pathological human locomotion in the framework of a collaborative Sinergia project funded by the Swiss National Science Foundation. The goal of the project is to develop, through machine learning and neuromechanical simulation, accurate models of human locomotion, together with Stephane Armand (University of Geneva, Kinesiology laboratory) and Auke Ijspeert (Biorobotics laboratory, EPFL, BIOROB). The project will (1) model pathological gaits resulting from motor impairments such as cerebral palsy, and (2) compare and combine neuromechanical simulation and machine learning approaches for gait analysis. It brings together expertise on pathological gait, neuromechanical simulation models, machine learning, coupled with a unique collection of relevant real world data. Continue reading

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Postdoc position on generative modelling for complex objects (closed)

We are looking for an excellent postdoc to work on the development of deep learning methods for the automatic composition of complex structures, such as sets, graphs, trees, sequences, that exhibit desired properties. Typical application scenarios include image and text generation, drug and molecule design. Research areas of direct interest include generative modeling, unsupervised and semi-supervised learning. Continue reading

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PhD position on Learning over distributed streaming data (closed)

We are looking for an excellent candidate who will undertake a PhD on the development of new machine learning methods for distributed streaming data generate in the context of the Internet of Things. Continue reading

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Postdoc position on Learning over distributed streaming data (closed)

We are looking for an excellent Postdoc to work on the development of new machine learning methods for distributed streaming data generate in the context of the Internet of Things. Continue reading

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PhD position on Machine Learning for representation learning (closed)

We are looking for an excellent candidate who will undertake a PhD on the development of new machine learning methods for non-parametric representation learning with an emphasis on two-level instance description problems and recommendation problems. Continue reading

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