Research Assistant (PhD) - salary grade E 13 TV-L Berliner Hochschulen
Excellence Cluster Science of Intelligence (SCIoI)
Reference number: SCIoI-C4-43B (starting not later than from 01/10/22 / for 3 years / closing date for applications 25/11/21)
The Technische Universität Berlin invites applications for a PhD position for the Cluster of Excellence “Science of Intelligence”.
What are the principles of intelligence, shared by all forms of intelligence, no matter whether artificial or biological, whether robot, computer program, human, or animal? And how can we apply these principles to create intelligent technology? Answering these questions - in an ethically responsible way - is the central scientific objective of the new Cluster of Excellence Science of Intelligence (https://www.scioi.de), where researchers from a large number of analytic and synthetic disciplines - artificial intelligence, machine learning, control, robotics, computer vision, behavioral biology, psychology, educational science, neuroscience, and philosophy - join forces to create a multi-disciplinary research program across universities and research institutes in Berlin. Interdisciplinary research projects have been defined (https://www.scienceofintelligence.de/research/projects), which combine analytic and synthetic research and which address key aspects of individual, social, and collective intelligence.
Working field
The doctoral project “Learning hierarchical regularities to structure policies for contact-rich robot manipulation” is part of the project “Generating Robust and General Real-World Behavior by Exploiting Regularities at Multiple Levels of Abstraction”
Efficient (deep) learning of complex, robust, and general robot manipulation is only possible with the inclusion of strong inductive biases. In this project, we explore the use of biases with a particular algorithmic structure, motivated by relevant knowledge about the visual system, for example, in biological systems. We will explore the hypothesis that suitable inductive biases represent highly structured regularities in the perception/action space. We investigate how such regularities can be identified and leveraged to learn behavior. We seek to understand how regularities at different levels of abstraction can be composed to form stronger, hierarchical inductive biases. The result of this project will be a powerful and data-efficient learning approach for complex behavior. We will develop and validate this learning approach in the context of contact-rich manipulation task on a highly capable hand/arm system with multi-modal sensors.
Responsibilities include scientific research within the project and academic services in the Cluster. PhD position includes the enrollment in the Cluster's doctoral program. All positions require participation in research colloquia, lecture series and workshops, as well as an active engagement in the Cluster's research activities.
Requirements:
- MS degree in computer science or similar field
- Research experience in robotics, machine learning, computer vision, and/or control
- Experience in Learning from Demonstration and force control desirable
- Experience in applying (deep) learning to control problems desirable
- Interest in interdisciplinary research in the context of the Cluster of Excellence “Science of Intelligence”
- Excellent software engineering and programming skills in Python and C++
- a good command of English and/or German, and a willingness to learn the missing language skills
Application procedure:
Candidates should upload their application (quoting the SCIoI Ref SCIoI-C4-43B) preferably via the portal http://jobs.scienceofintelligence.de to receive full consideration.
Applications should include: motivation letter, curriculum vitae, transcripts of records (for both BSc and MSc), copies of degree certificates (BSc, MSc, PhD if applicable), proof of English skills, abstracts of Bachelor-, Master- and (if applicable) PhD-thesis, list of publications and one selected manuscript (if applicable), two names of qualified persons who are willing to provide references, and any documents candidates feel may help us assess their competence.
Please click here for the official, legally binding German version of this job
Contact person: Prof. Dr. Oliver Brock
