Master Thesis in Deep Reinforced Cognitive Sensing for Enhanced Automotive Radar Perception
Master Thesis in Deep Reinforced Cognitive Sensing for Enhanced Automotive Radar Perception
Robert-Bosch-Campus 1, 71272 Renningen, Germany
Full-time
Robert Bosch GmbH
Company Description
At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives.
Our promise to our associates is rock-solid : we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.
The Robert Bosch GmbH is looking forward to your application!
Job Description
Cognitive sensing describes the idea of a sensor system actively engaging with its surroundings in a favorable manner. This research aims to address the challenges in Automotive Radars of detecting weak targets and vulnerable road users at long distances and in variable complex environments, overcoming the limitations of current static sensor modulations.
- During your master thesis, you will analyze and implement a reinforced cognitive model for radar, allowing for the adaptation of the sensor modulation based on the measured environment to enhance radar perception.
- You will extend the existing radar simulation to establish a closed-loop pipeline for online reinforcement learning.
- Finally, you will train a reinforcement learning agent optimizing sensor modulation parameters under different conditions and driving scenarios.
The results are to be evaluated and benchmarked against baseline methods in different use cases.
Qualifications
- Education : master studies in the field of Electrical Engineering, Simulation, Cybernetics or comparable
- Experience and Knowledge : profound knowledge of machine learning and radar technologies; coding experience in Python and deep learning frameworks, ideally PyTorch
- Personality and Working Practice : a communicative and analytical person, who is able to work independently and systematically
- Languages : good in English, German is a plus
Additional Information
Start : according to prior agreement
Duration : 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.
Need further information about the job?
Marius Schwarz (Functional Department)
49 173 5765310
Sherif Abdulatif (Functional Department)
49 711 811 14364
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