PhD – Robust Deep Learning
- Robert-Bosch-Campus 1, Renningen, Germany
- Legal Entity: Robert Bosch GmbH
Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology – with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.
The Robert Bosch GmbH is looking forward to your application!
Deep Learning is regarded as one of the key enabling technologies for autonomous driving. Analyzing existing algorithms with respect to their robustness is therefore vital for the development of safe products. The newly founded Bosch Center for Artificial Intelligence (BCAI) offers the perfect environment for PhD students to apply modern mathematical tools to machine learning problems and thus, going the next important step in making the human dream of autonomous driving a reality.
- Development and implementation of novel deep learning algorithms that is focused on provable robustness
- Applying primal-dual methods for (integer) linear programming and convex optimization to machine learning tasks
- Original research, collaboration with machine learning and optimization experts in Germany and the United States
- Publications in top-tier journals and at top-tier conferences
- Technical discussions and creation of new ideas within the research team at the BCAI
- Master of Science in computer science, mathematics, physics, or related fields with excellent grades.
- Profound knowledge of primal-dual methods for Linear Programming
- Basic knowledge of machine learning, preferably deep learning.
- Knowledge about the Fenchel-duality or the proximity operator is a plus, but not required
- Proven programming skills, preferably Python
- Strong English skills and willingness to travel to the United States and join our international academic partners
Duration: 3 years
The final PhD topic is subject to your university.
Need support during your application?
Kevin Heiner (Human Resources)
+49 711 811 12223
Need further information about the job?
Dr. Michael Pfeiffer (Business Department)
+49 711 811 18195