Edge AI Researcher - imec USA/University of Michigan Joint Postdoctoral Fellowship
What You Will Do
In many automotive applications, there is a need for efficient and fast (low-latency) processing of sensor data. This sensor data is key for, in general, (semi-)autonomous driving and for different ADAS features such as automatic braking, lane assist, and traffic assistance. Due to the success of AI in the last decade, AI algorithms are also increasingly being applied in this context. However, despite the successes, the cost and complexity of AI algorithms is constantly increasing in an unsustainable manner, surpassing the benefits of Moore's law. In addition, the pace of traditional hardware development cannot maintain the pace of performance and will become a bottleneck for the field. At the same time, embedding AI algorithms is far from trivial in a demanding applications such as automotive with stringent constraints like robustness, efficiency, safety, and resource consumption. There is thus a need for the adoption of novel compute paradigms, AI accelerators and hardware software co-design efforts that target the automotive application.
We are seeking a highly motivated postdoctoral researcher to address these issues and to set the pace towards hardware software co-design for ADAS features. The ideal candidate has an understanding of both AI algorithms and the underlying hardware architecture design. This role will be co-advised by an imec technical manager and a University of Michigan faculty member as part of a vibrant collaboration between imec and the University of Michigan. The position will be stationed at our new imec USA site located on Michigan University's campus in Ann Arbor, Michigan.
As the Successful Candidate
You will offer research and development support to advance exploratory research on novel architectures for edge AI algorithms in an automotive context. Specifically, you will 1) develop algorithms and hardware systems for efficient on-sensor, real-time processing of the asynchronous sensor events; and 2) develop end-to-end systems that integrate on-sensor frontends with compute-in-memory backend AI processors to handle a wide range of ADAS workloads. Collaborating with local teams at the University of Michigan, you will lead research activities on sensor suite selection, algorithm design and implementation, algorithm benchmarking, system architecture definition, and end-to-end architecture development and evaluation. Your lab research activities will synchronize with Imec teams in the US, Belgium, and Michigan.
These efforts will be a joint effort between University of Michigan and imec's automotive, architecture and AI labs. You will closely engage with different researchers and teams (hardware, sensor development, and other AI teams) to jointly come up with a full stack solution. Your work will take place in on the University of Michigan facilities as well as in imec research labs, collaborating with an international, multidisciplinary team. Regular participation and contributions to projects and team meetings is expected.
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