October 23, 2019; Claudia Widmann

FULLY-FUNDED PHD POSITION IN APPLIED MACHINE LEARNING
- Data-integrated Simulation of Human Perception and Cognition -

The Chair for Human-Computer Interaction and Cognitive Systems at the University of Stuttgart, led by Prof. Dr. Andreas Bulling, invites applications for a fully-funded PhD position in Applied Machine Learning. The position is situated in the context of the DFG Excellence Cluster Data-Integrated Simulation Science (SimTech), in an environment that offers much creative freedom and support to conduct cutting-edge research.

QUALIFICATIONS

A successful candidate has demonstrated outstanding academic performance (rank at top of class) and a strong technical background in one or both of the following areas:

  • Machine learning, e.g. deep and recurrent neural networks, generative models, visual question answering or captioning, cognitive modelling
  • Human-Computer Interaction, e.g. design and evaluation of interaction techniques, user interface and user experience design, empirical evaluation of interactive systems

A strong interest in applying these methods to human-computer interaction, for example intelligent user interfaces, is required. Excellent programming skills are expected. Previous experience with Python, TensorFlow, or CUDA is an advantage. Strong team working and critical thinking skills, aptitude for independent and creative work, as well as fluent English written and presentation skills are essential.

POSITION

We offer a fully-funded PhD research position with a flexible start date. Salaries are internationally competitive based on state employee salary scheme TVL-E13 (100%) that includes health insurance, social insurance, and contributions to the retirement pension plan. You will develop, implement, and evaluate new computational methods, as well as write up the results for academic publication at top international venues, such as CVPR, ICCV, ECCV, or NeurIPS. You will contribute to the leadership of ongoing projects, will have the opportunity to advise undergraduate and graduate students, and contribute to the teaching activities of the group.

ABOUT THE GROUP

The Perceptual User Interfaces group works at the intersection of computer vision, applied machine learning and human-computer interaction. The group develops computational methods as well as ubiquitous and wearable systems to address fundamental challenges in sensing, modelling, and analysing everyday non-verbal human behaviour. The group is well-known for this line of work, has a strong presence in leading conferences in the above fields, and publications from the group are frequently distinguished with best paper awards (16 in the last four years). You will work among gifted colleagues and experienced scientists and have access to excellent infrastructure. For details see: https://www.perceptualui.org/

APPLICATIONS

Applications must be submitted by email and include a cover letter (describing research experience, fit for position and future interests), a CV, study transcripts, copies of high-school degrees, and contact information of two references. The application should also indicate earliest date of availability. Applications are considered until the position has been filled.

Please send your application to hcics-application@vis.uni-stuttgart.de

Should you have questions about the position, please contact Prof. Dr. Andreas Bulling https://www.perceptualui.org/people/bulling/

Looking for an Expert?

The Project Leaders of the SFB-TRR 161 are experts in the field of visual computing. Just get in touch directly.

If you need help to find the contact for your inquiry please contact the Public Relations Team.

BOGY in der Forschung?

Du möchtest schon während der Schulzeit die Welt der Forschung kennenlernen? Du möchtest dich über die Studiengänge an unseren Transregio Partnern informieren? Du programmierst gerne oder interessierst dich für Informatik und Computergrafik?

Ein BOGY im SFB-TRR 161 gibt dir die Chance, dich mit unseren Forschern auszutauschen und in die Arbeitswelt der Wissenschaft einzutauchen.

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