Research Assistant / Postdoc (f/m/d) Electrical Engineering and Computer Science
Published(30 days ago)
Deadline for applications(4 days left)
Technische Universität BerlinBerlin
Technische Universität Berlin offers an open position:
Research Assistant - Postdoc - salary grade E 13 TV-L Berliner Hochschulen
part-time employment may be possible
The Technische Universität Berlin invites applications for a Postdoc 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 (www.scienceofintelligence.de/research/projects),
which combine analytic and synthetic research and which address key aspects of individual, social, and collective intelligence.
Faculty IV - Electrical Engineering and Computer Science Reference number: SCIoI-41/19 (starting at 01/10/19 / for 3 years / closing date for applications 30/06/19)
Working field: Project: Knowledge-augmented face perception
Post-doctoral project: Synthesizing knowledge-augmented face perception
Face perception and categorization is fundamental to social interactions. In humans, input from facial features is integrated with top-down influences
from other cognitive domains, such as expectations, memories and contextual knowledge.
In contrast to human perception, automatic systems of face processing are typically based purely on bottom-up information without considering factors as
prior knowledge. The aim of this project is therefore to bridge the gap between human and synthetic face processing by integrating top-down components typical
for human perception into synthetic systems. The results of experiments involving human subjects in combination with video recordings will be used in deep learning
training procedures aiming at the development of computational models.
Conducting experimental research in computer vision
Interaction within the SCIoI cluster of excellence
Compilation of the results for presentations, project reports, and publications
All positions require participation in research colloquia, lecture series and workshops, as well as an active engagement in the Cluster's research activities.
Requirements: Applicants must hold a PhD degree in Computer Science, Computer Engineering or related engineering disciplines and should have proven skills/background in following topics:
Computer vision and image analyses
In depth programming skills (C/C++, Python)
Laboratory experience using cameras and robotic camera platforms
Strong interest in psychology, visual perception and machine learning
Good command of the English language (spoken and written).
Applications should include: motivation letter, curriculum vitae, transcripts of records (for both BSc and MSc), copies of degree certificates (BSc, MSc, PhD if applicable),
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 send your written application with the reference number to Technische Universität Berlin - Der Präsident - Fakultät IV,
Institut für Technische Informatik und Mikroelektronik, Computer Vision & Remote Sensing, Prof. Dr.-Ing. Hellwich, Sekr. MAR 6-5, Marchstr. 23, 10587 Berlin or
by e-mail to email@example.com.
To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities
will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.
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