[visionlist] [jobs] Neural Network models for language and interactive robots

Wermter, Stefan wermter at informatik.uni-hamburg.de
Tue Dec 10 14:25:07 -04 2019

The Department of Informatics, Institute of Knowledge Technology, 
invites applications for multiple positions as

RESEARCH ASSOCIATES (Postdocs and PhD Students) in the context of the 
CROSSMODAL LEARNING: Neural network models for language and interactive 

Positions commence from January 2020 or as soon as possible thereafter 
and are in accordance with Section 28 subsection 3 of the Hamburg higher 
education act (Hamburgisches Hochschulgesetz, HmbHG) on SALARY LEVEL 13 

These are fixed-term contracts in accordance with Section 2 of the 
academic fixed-term labor contract act (Wissenschaftszeitvertragsgesetz, 
WissZeitVG). The term is fixed for up to 4 years until 31st of December 
2023. The full-time positions call for 39 hours per week.


Duties include academic services in the project named above. Research 
associates may also pursue independent research and further academic 

Specific Duties:

Duties in the project include the design, development and evaluation of 
neurocognitive models of crossmodal language learning as well as 
neurorobotic models for crossmodal joint attention and social 
interaction. The overall project aims to deepen interdisciplinary 
research between computer science, neuroscience, and psychology in order 
to set up collaborative research with a focus on 
human-robot-collaboration, artificial intelligence, neuroscience and 
psychology while focusing on the topic of cross-modal learning. The 
long-term challenge is to understand the neural, cognitive and 
computational evidence of cross-modal learning and to use this 
understanding for (1) better analyzing human performance with 
cross-modal correspondence and (2) building effective cross-modal 
computational and robot systems.


A university degree in a relevant subject. For doctoral positions, 
academic degree of MSc in computer science, computer engineering or 
similar. For post-doctoral positions, a doctorate, or equivalently the 
experience of more than three years of doctoral studies plus 
publications in the area of Intelligent Systems are required. The degree 
must qualify the post holder to carry out the above-mentioned duties. 
Programming skills in some of Python, C, ROS, Tensorflow or PyTorch are 
required. Your demonstrated research interests should be in some of the 
areas of Intelligent Systems (e.g. Neural Networks, Robotics, Machine 
Learning, Speech, Vision, or Affective Processing). International 
publication experience is expected. Very good communication skills in 
English are expected.

The University aims to increase the number of women in research and 
teaching and explicitly encourages qualified women to apply. Equally 
qualified female applicants will receive preference in accordance with 
the Hamburg act on gender equality (Hamburgisches Gleichstellungsgesetz, 

Qualified disabled candidates or applicants with equivalent status 
receive preference in the application process.

As a University of Excellence, Universität Hamburg is one of the 
strongest research universities in Germany. As a flagship university in 
the greater Hamburg region, it nurtures innovative, cooperative contacts 
to partners within and outside academia. It also provides and promotes 
sustainable education, knowledge, and knowledge exchange locally, 
nationally, and internationally.

For further information, please contact Prof. Dr. Stefan Wermter or 
consult our website at: https://www.informatik.uni-hamburg.de/wtm/

Applications should include a cover letter, a tabular curriculum vitae, 
pdf of best publications, and copies of degree certificate(s). Please 
send applications by 15.01.2020 or until the post gets filled to Ms 
Katja Koesters (katja.koesters at informatik.uni-hamburg.de) in a single 
pdf document.

Professor Dr. Stefan Wermter
Director of Knowledge Technology
Department of Informatics
University of Hamburg
Vogt-Koelln-Str. 30
22527 Hamburg, Germany

Email: wermter AT informatik.uni-hamburg.de

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