Master Thesis Researcher: Deep Learning and Graph Neural Networks

hace 3 días


Madrid, Madrid, España Kollmorgen Automation Ab A tiempo completo
About the Role

We are seeking a highly motivated Master Thesis Researcher to join our team at Kollmorgen Automation Ab. The successful candidate will have the opportunity to apply Deep Learning to a real-world problem, researching novel representation of graph data.

  • Collaborate with domain experts to represent traffic rules in a graph-like data structure.
  • Construct training datasets by modifying real AGV system layouts and augmenting with synthetic data.
  • 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.

Working with Us

  • We will provide computers and great support from your supervisor and other colleagues.
  • All students are compensated after the thesis is submitted and the final work meets the quality standard that is generally accepted by the university and presented at Kollmorgen.
  • Send in your application by submitting a CV and/or information about your studies and a short sentence about why you find this project interesting.

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