European Training Network REPAIRS kicks off on February 4, 2021.
- Prof. Dr. Gregor Schöner
- February 2, 2021
REPAIRS is an acronym for RE-learning Perception-Action In Rehabilitation from a Systems perspective. In REPAIRS 15 PhD positions are available that study learning in perception-action on different levels of the perception-action cycle. Two of those positions will be housed at the INI-RUB (Projects 1 and 9). [Note: to be eligible for the two positions at RUB, potential students must NOT have resided inside Germany for longer than 12 months in the three years prior to recruitment.]
REPAIRS is a European Training Network (ETN) within the H2020 Marie Sklodowska-Curie Innovation Training Network programme, funded by the European Union. REPAIRS aims to improve the effectiveness of rehabilitation that is concerned with the restoration and enhancement of functional ability and quality of life of people with a movement disorder or disability related to perception and action. To this end REPAIRS combines insights from fundamental research on how individuals re-learn perception and action with cutting-edge rehabilitation practice using a systems perspective. Projects will cover a broad range of disciplines, ranging from human movement science, rehabilitation, behavioural sciences, engineering, machine learning, mathematical modelling at neural and behavioural level, to philosophy. The REPAIRS network consists of 20 partners (academic partners, clinical partners, industrial partners and patient organisations) to provide innovative training-through-research preparing the ESRs to become the next generation of creative, innovative and leading academic and entrepreneurial researchers.
Description of the project
Details about programs, projects, and how to apply
The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.
Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany
Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210