Academic Staff Member - PhD Thesis: Model Compression for Resource Efficiency | Akademische*r Mitarbeiter*in - PhD thesis / Doktorarbeit: Model compression for resource efficient

Job Summary

This role is a unique opportunity for an Academic Staff Member to pursue a PhD thesis focused on Model Compression for Resource Efficient Deep Learning within the 'Lab2Device' research project at Offenburg University of Applied Sciences. The successful candidate will independently conduct research tasks, publish findings, and translate research results into functional applications, while also guiding students. The core objective is to develop novel Model Compression techniques (such as quantization, pruning, and knowledge distillation) that minimize resource consumption (memory, latency, energy) on embedded systems with minimal impact on model performance. Working in an interdisciplinary team, this position is ideal for someone with strong programming skills, practical experience in modern Machine Learning frameworks, and an interest in creative, interdisciplinary problem-solving.