Research Scientist: Graph Neural Networks for Predictive Traffic Modeling
hace 4 semanas
About the Project
At Kollmorgen Automation Ab, we are seeking a highly skilled Research Scientist to contribute to our cutting-edge project on Graph Neural Networks for predictive traffic modeling in Automated Guided Vehicles. This project aims to accelerate the deployment of automation in intralogistics and improve user experience.
Background
An Automated Guided Vehicle (AGV) system is a fleet of mobile robots that transport goods in a network of fixed virtual roads. The network must handle the intended traffic load without traffic jams, verified by running simulations. However, such simulations are time-consuming, and faster feedback would directly translate to decreased cost in these automation projects.
Goal of the Thesis
Your job will be to continue the work of three previous master thesis projects, carried out in 2023 and 2024. The first thesis used Graph Neural Networks to predict the traffic score of an intersection, the second thesis predicted the wait time associated with each individual road segment, and the third one investigated the generalization capabilities of these models by applying it to more diverse datasets.
Method
Construct training datasets by modifying real AGV system layouts and augmenting with synthetic data. Collaborate with domain experts to represent traffic rules in a graph-like data structure. Experiment with deep learning architectures, focusing on Graph Neural Networks. Perform model selection and hyperparameter tuning. Evaluate model robustness and reliability using techniques like K-fold cross-validation.
About You
Hold a Bachelor Degree in Computer Science, Applied Mathematics or similar. Enrolled in relevant master program such as Algorithms, Engineering Mathematics, Complex Adaptive System or Data Science/AI. Completed courses in Machine Learning and statistics. Had previous work experience as programmer. Had experience of Python, including libraries such as numpy, pandas, sklearn and pytorch/tensorflow. Experience of research is meritorious.
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