Applications are invited for several full-time PhD and postdoctoral research positions in the areas of Human-Computer Interaction, Computer Vision, and Applied Machine Learning in the Department of Computer Science at the University of Stuttgart, Germany.
Positions are fully funded, in part by an ERC Starting Grant.
A successful candidate has a strong technical background in one or both of the following areas:
- Machine learning, e.g. deep learning, generative models, (inverse) reinforcement learning
- Computer vision or graphics, e.g. egocentric vision, 3D face modelling, scene understanding,
pose estimation, object detection/recognition
A strong interest in applying these methods to human-computer interaction, for example intelligent user
interfaces, cognitive systems, or computational interaction, is required.
Excellent programming skills in C++ or similar languages are expected. Experience with Python,
MATLAB, or CUDA is beneficial.
Fluent English written and presentation skills are essential.
ABOUT THE UNIVERSITY OF STUTTGART
The University of Stuttgart is cradled in what is simultaneously one of Germany’s most beautiful
landscapes and one of Europe’s most economically successful areas. The region is known for a high
standard of living, beautiful surroundings, and easy access to other major metropolitan areas. The
university is one of the top nine leading and oldest technical universities (TU9) in Germany and
consistently ranked among the world’s best universities in international rankings. The University of
Stuttgart is part of the Cyber Valley initiative (https://cyber-valley.de/en), a new center for artificial
intelligence research that brings together partners from science and industry to boost intelligent systems
research and development in the Stuttgart-Tübingen region, specifically in the areas of machine learning,
robotics, and computer vision.
The Department of Computer Science is located on the university campus in Stuttgart Vaihingen. It is
devoted to cutting-edge research in computer science ranging from foundations (algorithms,
programming logics, computer architecture) to a variety of application domains (computer vision and
graphics, machine learning and robotics, intelligent systems). With its vibrant research environment and
its attractive Bachelor and Master programs, the Department attracts top students from all over the
world. The department offers a stimulating, competitive, and collaborative work environment. It is
equipped with high-class research facilities and has links to leading international companies in and
around Stuttgart (e.g. Bosch AI, Mercedes-Benz, Porsche).
ABOUT THE GROUP
The newly established research group, relocating from the Max Planck Institute for Informatics in
Saarbrücken and headed by Prof. Dr. Andreas Bulling, works in the fields of computer vision and applied
machine learning with applications in human-computer interaction, cognitive systems, as well as
wearable and ubiquitous computing. The group develops computational methods as well as ambient and
on-body systems to address fundamental challenges in sensing, modelling, and analysing everyday nonverbal
human behaviour, in particular human gaze and body language. The group is well-known for this
line of work, has a strong presence in leading conferences in the above fields, and work from the group is
regularly being distinguished with best paper awards. You will work among gifted students and
experienced scientists from all over the world; and have access to excellent infrastructure, including
several regular series of tutorials, lectures, journal clubs and invited talks by international guests, as well
as a high-performance GPU cluster.
For details see our previous group website: https://perceptual.mpi-inf.mpg.de/
Applications and inquiries should be sent quoting reference number 42.2018 to Prof. Dr. Andreas Bulling
(see contact details below). Applications must be submitted by email as a single pdf (max. 10 MB) and
include a CV, motivation letter with research statement, publication list, transcripts of BSc and MSc
degrees, and contact details of 2-3 references. Optionally, up to 2 selected own publications or theses
can be included in a second pdf (max. 5 MB). Applications should also indicate earliest date of availability.
There is no fixed application deadline; applications are considered until the positions have been filled.