Research Intern - Austin, TX (Summer 2020)
- Speedway, Austin, TX, USA
- Legal Entity: Robert Bosch LLC
Robert Bosch LLC is an international, non-profit-owned company with ~$85B revenue per year. Many know it best for its appliances and power tools, but Bosch also happens to be the largest automotive supplier in the world, with its vehicle subsystems in nearly 100% of vehicles being made today. Bosch offers just about every subsystem that goes into a car today, from windshield wipers to engine control units. It already sells or is developing every sensor and in-car computer required for an autonomous vehicle. Bosch has advanced projects at various levels of autonomy, from driverless Level 4 down to driver assistance products that are already in production vehicles, such as automatic emergency braking and lane-keep assist.
The Austin office offers an R&D experience that's heavy on the R. We have the flexibility to apply machine learning to existing driver assistance products that are already saving lives on the road, to apply it to Bosch's full autonomy projects, and to conduct peer-reviewed research collaborations with UT Austin and other top academic institutions that focus on any level of autonomous driving systems.
We pay competitive salaries in a vibrant city that's comparatively affordable to live in. *We are dedicated to creating a diverse Austin team and a family-friendly work culture.*
In short, we find and work on high-impact autonomous driving problems at Bosch that have not necessarily been viewed yet through the lens of a machine learning researcher.
If selected, you will be part of our team at the new Bosch Austin site. The site is embedded in the University of Texas at Austin's Computer Science Department, with offices in the CS Department's beautiful new Gates Dell Complex.
As part of your application process, we will together find a research project for you to work on during the period of the internship. Depending upon your interests and experience, your research project could either be collaborative research towards a peer-reviewed publication or applied R&D that contributes to Bosch's autonomous driving projects.
We want to hear from you if you have begun publishing in reinforcement learning or learning from demonstration, enjoy collaborating and communicating about your work, and are comfortable moving between settings of fundamental research and applied R&D.
One or more of the following: (1) Collaborate on research projects involving the usage of machine learning to improve the decision making of state-of-the-art autonomous driving and driver assistance systems. Research activities will span collaborating on fundamental topics---where autonomous driving may only be one application of your work---and applied topics. (2) Contribute to the development, implementation, or evaluation of algorithms that can be applied to existing Bosch autonomous driving projects, including adapting research code to be application compatible. (3) Support fundamental research project(s) through software design and programming
Contribute to the writing and publication of peer-reviewed research
Become part of the UT Austin Computer Science community, attending research group meetings and lectures as well as discussing ideas with university colleagues
Currently pursuing a degree with a focus on robotic learning, reinforcement learning, learning from demonstration / behavioral cloning / imitation learning, or planning for navigation
- Must be currently enrolled in an accredited university
- Pursuing a Masters degree with at least one semester completed
- Graduate Student only
- Minimum of overall GPA of at least 3.0
- Must be a minimum of 18 years of age
Be pursuing a graduate degree in one of the fields listed above
Strongly preferred: Excellent communication skills, both written and verbal
Strongly preferred: Adept at C++ or Python programming in the context of machine learning development
Strongly preferred: Past publication in related fields
Expert in general software development within complex system architectures and varied toolsets
Experience designing and implementing deep learning algorithms for sequential decision-making
Knowledge of common automated-driving algorithms, including algorithms for perception and behavior generation
Knowledge of driver assistance technologies
More general expertise in automotive systems: experience with vehicle and system test-release procedures in automotive or related industries; experience in embedded automotive systems; and understanding of vehicle architecture and vehicle interfaces
By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics) Initiatives:
FIRST Robotics (For Inspiration and Recognition of Science and Technology)
AWIM (A World In Motion)