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Master's Thesis Opportunity in Neural Network Inference Optimization

vor 1 Monat


Ingolstadt, Bayern, Deutschland Fraunhofer-Gesellschaft Vollzeit

Research Opportunity in Neural Network Inference Optimization

We are seeking a highly motivated and skilled Master's student to undertake a research project focusing on developing innovative techniques to enhance the efficiency and performance of neural network inference. The project will involve researching and analyzing cutting-edge inference optimization methods for neural networks, designing and implementing innovative approaches to enhance inference speed and efficiency, and collaborating with our research team to validate proposed methods on various real-world use cases.

Requirements

– Enrolled in a Master's program in computer science, electrical engineering, physics, mathematics, mechanical engineering or related fields

– Strong background in machine learning and deep learning

– Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch)

– Knowledge in inference optimization techniques and frameworks (e.g., TensorRT)

What We Offer

– Opportunity to work in the field of machine learning and neural networks

– Access to state-of-the-art computational resources and modern infrastructure

– Valuable research experience and exposure to real-world practical projects

– Flexible working hours

– Potential for co-authorship on research papers and conference presentations

Fraunhofer is a leading research organization in Europe, and our research efforts are geared towards addressing real-world challenges. We value diversity and promote equal opportunities for all employees.