PhD position on learning and simulation for human locomotion modelling
The data mining and machine learning group has 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.
Human locomotion is a highly complex dynamical system and learning locomotion models is a challenging task.
Pathological locomotion modelling is even more challenging due to the limited availability of training data.
This project will address these challenges by bringing together machine learning and neuromechanical simulation.
On the machine learning side we will explore a number of research problems such as learning of dynamical systems
using conditional generative models, learning with simulated data, learning, tunning and improving simulators. A
simulator is a model of domain knowledge and as such it can be imprecise and incomplete. We are particularly interested
in the tight integration of simulation and learning and their interactin in a virtuous cycle with each one improving
the other; relevant work includes
interaction networks
and the neural physics engine.
The position is funded by SNSF for four years.
The successful candidate will join the Data Mining and Machine Learning
group at the Department of Information Systems of University of Applied Sciences,
Western Switzerland, led by Prof. Alexandros Kalousis, and will enroll as a PhD
student at the Computer Science department of the University of Geneva within
the VIPER group led by Prof. Stephane Marchand-Maillet.
Our research explores a number of different issues such as: learning in high dimensional
settings, dimensionality reduction and feature selection, learning with structured data
(multiple kernel learning), metric and similarity learning, the exploitation of domain
knowledge in the learning process. For a more detailed description the interested candidates
may take a look at: http://cui.unige.ch/~kalousis/
and the list of publications
within there. The greater Geneva lake area is a world-renowned education and research hub,
including not only the University of Geneva, but also EPFL, and IDIAP. It offers considerable
opportunities for training and exposure to data mining and machine learning, with a number of
research teams being active on these and related fields. In addition the selected candidate
will have ample opportunities to participate in the main ML and DM conferences. The ideal candidate will have:
Candidates should send:
Application Deadline
Priority will be given to applications received by the 28th of February 2018, however applications will be accepted until the position is filled. The position status will be indicated here.
The position will be available from the 1st of September 2018.