Jobs

HiWi positions

HiWi for Revision of CG1-assignment Framework

We are looking for motivated students that want to contribute to the ongoing revision of the CG1-assignment framework. The successful candidate will work on the provided ray-tracing framework, unit and integration tests as well as the practical assignments. Perspectively, this may lead to a tutor position for the next winter term 2018/19.

If you are interested to apply, please contact Stefan Lemme

HiWi for Global Illumination for Interactive Planning Tools of Furnishing

We are looking for motivated students that join our team to work on our high-performance ray-tracing framework with support for global illumination. The successful candidate will work on rendering-support services based on our ray-tracing framework to be integrated into the set of interactive planning tools of a commercial partner.

If you are interested to apply, please contact Stefan Lemme

HiWi for Motion Synthesis Demonstrator Development

We are looking for a student to help with the development of demonstrators for our existing motion synthesis solutions using Unity. Optionally the student can also work on the development of an animation viewer for the web browser that can be based on Unity or XML3D. The online viewer would be used to demonstrate the state of our motion models in user studies and to project partners.

If you are interested to apply, please contact Erik Herrmann

Researcher positions

Researcher for Compiler and Language Design for High-Performance Ray-Tracing

We are looking for a highly motivated PhD student that joins our team to work on our high-performance ray-tracing framework with support for global illumination. The successful candidate will work on new methods to parallelize the renderer on heterogeneous platforms and to distribute the computation across multiple nodes using new compiler technologies.

If you are interested to apply, please contact Dr.-Ing. Richard Membarth

Researcher for Cross-Platform Convolutional Networks for Deep Learning

We are looking for a highly motivated PhD student that joins our team to work on a new deep-learning framework. The successful candidate will work on new methods to represent tensor operations that allow optimizations across single network operators/layers and efficient code generation for CPUs/GPUs.

If you are interested to apply, please contact Dr.-Ing. Richard Membarth