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<p>Technische Universität Berlin invites applications for a PhD
position
for the Cluster of Excellence "Science of Intelligence". <br>
</p>
<p>Please apply at <br>
</p>
<a class="moz-txt-link-freetext" href="https://www.scienceofintelligence.de/call-for-applications/open-positions/ref-scioi-c3-31b/">https://www.scienceofintelligence.de/call-for-applications/open-positions/ref-scioi-c3-31b/</a><br>
<br>
<br>
<strong style="background: 0px 0px; border: 0px; margin: 0px;
outline: 0px; padding: 0px; vertical-align: baseline;">Working
Field: Social responsiveness and its effects on learning in
human-human and human-robot interaction</strong><br>
<p>This interdisciplinary research projects combines research from
educational psychology and computer vision to examine principles
of social responsive teaching behaviors in social learning
situations. Perceiving and appropriately reacting to social cues
facilitate effective knowledge transfer between interaction
participants, whether they be humans or humans and an artificial
agent such as a robot. The main goal of this project therefore is
to develop synthetic systems (robotic teaching assistants) with
high-level perceptual capabilities in social learning situations
and, in the course of that, synthetic systems that are able to
simulate social responsive behaviors.</p>
<p><br>
</p>
<p><strong style="background: 0px 0px; border: 0px; margin: 0px;
outline: 0px; padding: 0px; vertical-align: baseline;">Doctoral
project: “Perception, Categorization and Synthetization of
social responsiveness in human-human and human-robot interaction
during learning situations”</strong><br>
</p>
<p>The project focuses on the identification of teaching behaviors
that can be labeled as ‘social responsive’ in learning situations.
We aim to automatically understand relations between social
responsive teaching behaviors and student engagement, emotion, and
cognitive performance in Human-Human and Human-Robot interaction.
One aim is to sensitively categorize behaviors that define social
responsive teaching behaviors, to synthesize such behaviors and to
apply synthesized behaviors in learning situations using robotic
teaching assistants.</p>
<br>
<br>
<b>Duties: </b><br>
<br>
- Conducting experimental research in computer vision <br>
- Analysis of video data to generate algorithms for computer vision
<br>
- Automated evaluation of behavior
<br>
- Modeling of behavior using representation and reinforcement
learning
<br>
- Interaction within the SCIoI cluster of excellence
<br>
- Compilation of the results for presentations, project reports, and
publications<br>
<br>
<br>
<b>Requirements: </b>Applicants must hold a Diploma/Master’s degree
in Computer Science or related sciences and should have proven
skills/background in following topics:<br>
<br>
- profound expertise in computer vision and machine learning<br>
- expertise in robotics and visualization<br>
- excellent mathematical skills,<br>
- in depth programming skills (C/C++, Python, Matlab),<br>
- very good command of English, both written and spoken,<br>
- a keen interest in understanding intelligence,<br>
- the strong communicative skills required for interdisciplinary
research,<br>
- a conscientious work approach, flexibility, good time management,
and ability to work in a team<br>
<br>
<br>
<b>Application procedure:</b> Candidates should upload their
application preferably via the portal<span> </span><font
color="#000000"><a href="http://www.scienceofintelligence.de/jobs"
style="background: rgba(0, 0, 0, 0) none repeat scroll 0px 0px;
border: 0px none; margin: 0px; outline: currentcolor none 0px;
padding: 0px; vertical-align: baseline; text-decoration: none;
transition: color 0.2s ease-out 0s; font-style: normal;">www.scienceofintelligence.de/jobs</a><span> </span>in
order to receive full consideration.<br>
Applications should include: motivation letter, curriculum vitae,
transcripts of records (for both BSc and MSc), copies of degree
certificates (BSc, MSc), abstracts of Bachelor-, Master-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.</font>
<pre class="moz-signature" cols="72">--
Prof. Dr.-Ing. Olaf Hellwich
Technische Universität Berlin, Computer Vision @ Remote Sensing
MAR 6-5, Marchstr. 23, D-10587 Berlin, Germany
Tel. +49(0)30/314-22796; <a class="moz-txt-link-freetext" href="http://www.cv.tu-berlin.de">http://www.cv.tu-berlin.de</a></pre>
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