Job Description

The expected candidate will engage in a broad spectrum of cutting-edge research in areas at the intersection of applied cryptography, security, system security, and AI for security. We are particularly interested in candidates that can demonstrate through their research work experience in the application of AI techniques and methods to solving challenging security and privacy problems. The successful candidate is expected to:

• Drive research projects spanning a wide variety of topics and domains including but not limited to cyberdefense, automotive system security, industrial control system security, privacy for data intensive applications, and security in distributed systems
• Positively impact the future business of Bosch from the invention of novel technologies and intellectual property through their successful transfer to business units for realization in real products
• Collaborate closely with top-tier research universities in the US (e.g. Carnegie Mellon University) to help bring cutting-edge R&D results out of the lab and into the market
• Shape Bosch's future R+D strategy via identification of early-stage trends and technologies via active scouting of the overall scientific/technical environment

Qualifications

Required Qualifications:

• Ph.D. in computer science, computer/electrical engineering, or related field
• Experience in security and privacy research showing the ability for novel results and, at the same time, to build prototypes and verify experimentally theoretical designs.
• Experience in solving problems at the intersection of security and machine learning/AI (i.e., LLMs), and in particular, the application of modern AI techniques, tools and method to solve challenging security and privacy problems, such as, intrusion detection, anomaly detection in security applications, network security, and applications of data mining to/in constrained environments (e.g., automotive networks) for security

Preferred Qualifications:

• Experience in at least one of the following areas as evidenced by significant contributions in the form of publications and/or patents or patent applications:
  • System Security, network security, hardware, embedded security, side-channels, trusted computing and secure execution environments (e..g, SGX, ARM TrustZone, etc.)
  • Privacy enhancing technologies, Zero knowledge proofs, MPC, differential privacy, etc.

NOTE: Candidates familiar with a second area (should be able to understand and contribute in deep technical discussions in the first area) are particularly encouraged to apply.

• Publications or graduate-level coursework in Deep Learning/Reinforcement Learning /Generative Models, LLM-focused security, adversarial ML, etc.. Fluency in ML libraries such as Pytorch, TensorFlow, SKLearn, Hugging, Face Transformers, etc. as evidenced to open source projects or similar.
• Fluent in at least one high-level programming language (e.g., C/C++, python, etc.). Experience with low level programming (assembly) or HDL a plus.
• Excellent communication and presentations skills, including the ability to effectively convey complex technical topics to non-subject matter experts

Additional Information

** Equal Opportunity Employer, including disability / veterans**

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.

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