We are seeking a motivated and talented PhD student with interest and skill in physically-based simulation, distributed/parallel computing, and/or machine learning techniques. The main focus will be on the development of machine learning methods for balancing distributed computations in surgical simulation. The work will address techniques capable of autotuning for time-critical complex biomechanical simulations on parallel systems. A key difficulty is the dynamically changing requirements of simulation components.
Candidates should have earned a degree in Computer Science, Physics, Applied Mathematics or other related fields. Good knowledge in physically-based simulation is expected. In addition, some experience with machine learning methods is of advantage; knowledge of medical applications is also a plus. Experience and knowledge in C/C++ programming is expected, as well as a good level in English, both written and spoken.
The position is open immediately. It is offered on the level of a nonpermanent university research student at a 100% salary rate. Successful candidates will become employees of the University of Innsbruck with full social security coverage under Austrian national law. A detailed description of the program, of the required qualifications, and additional details about applications can be found at http://docc.eu/.
group has many years of experience in research related to surgical simulation, computer haptics, augmented reality, and advanced interfaces. The University of Innsbruck, founded in 1669, is a public institution, located in the capital of the Austrian federal state of Tyrol, beautifully situated within the Alps.
- Candidates should prepare application documents according to the requirements outlined at https://www.uibk.ac.at/projects/dp-docc/application/
- Deadline for application is September 10th, 2019. For further questions and coordination, please get in touch with: Prof. Dr. Matthias Harders, Computer Science, University of Innsbruck, Austria
- Web: http://igs.uibk.ac.at/