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1) postdoc (2 years) in machine learning and embedded systems

this project addresses real-time execution of concurrent multi-dnn workloads. deep neural networks (dnn) are widely deployed in resource-constrained embedded devices with limited processing and storage capabilities.  there are many industry frameworks for supporting efficient dnn inference on resource-constrained embedded devices, but they do not address concurrent execution of multiple dnns. multi-dnn workloads bring additional challenges of resource contention due to sharing of common pus, and requires novel scheduling and coordination algorithms to ensure qos (quality-of-service) for each dnn in a multi-dnn workload.

2) postdoc (2 years) in real-time systems

this project addresses the general area of real-time embedded systems. research topics include real-time scheduling theory, mixed-criticality systems, real-time multicore systems, real-time systems design, probabilistic timing analysis, safety and security issues, etc, with applications in safety-critical autonomous systems such as autonomous driving.

the specific topic will be determined by considering both the applicant¡¯s research background and project requirements. please contact prof. gu at zonghua.gu @ umu.se with your resume.
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