Objective
Training site fellowships in Advanced Studies for Autonomous Robotic Systems Dept. of Technology , Oerebro University
DESCRIPTION OF THE RESEARCH TRAINING AREA
The PhD training is in core technologies for autonomous robotic systems: perception, action, and reasoning. Perception is done by sensor hardware, including biomorphic sensors, and perceptual routines able to identify objects, events, and processes. Action provides motion and manipulation via the integration between perception and control - it incorporates perceptual routines and adapts to variations in these. Reasoning provides the connection between perception and action - it interprets perceptual data and translates it into actions to achieve a goal. Advanced aspects include:
1 ) integration of core technologies for acting in unstructured/uncertain environments; and
2) technologies enabling learning and adaptation and co-operative behavior. We encourage applications from fellows specializing in computational perception (sensors/sensing, intelligent data analysis); AI for robotics (e.g. reasoning under uncertainty, planning, scheduling, machine learning); robot kinematics and dynamics, and perception-based control of motion and manipulation.
EXPERIENCE REQUIRED
Candidates should be enrolled in PhD studies in their home institutions in one of the following areas: AI, electrical and electronic engineering, robotics/automation, signal processing/estimation, computer science.
RECRUITMENT PLAN
We will receive 8 fellows over a 4 years period. Each fellowship is between 3 and 12 months. A total of 48 person/month will be awarded. Applicants should contact Prof. Dimiter Driankov, Dept. of Technology, Oerebro University, 70182 Oerebro, Sweden, Dimiter.Driankov@tech.oru.se, tel +46-19-303799. Oerebro University is an equal opportunity employer. Applications from female candidates are strongly encouraged.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences data science
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering signal processing
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics autonomous robots
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
701 82 OREBRO
Sweden
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