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BMBMW Group

Thesis Map Matching and Path Prediction for Autonomous Driving(m/w/x)

Ulm
Full-timeWith Home Office
AI/ML
Data Science

Modeling road connectivity in RDF and implementing rule sets for path computation. Machine learning background and Python/ML framework experience required. Mobile work, flexible hours, student apartments.

Requirements

  • Studies in computer science, data science, or related field
  • Solid background in machine learning
  • Experience with Python and ML/DL frameworks
  • Familiarity with graph representations and knowledge graphs
  • Understanding of graph neural networks or representation learning
  • Software engineering skills for reproducible experiments
  • Good German and English skills

Tasks

  • Support modeling road connectivity and constraints in RDF
  • Implement rule sets for computing probable paths
  • Build features from observations and road graph
  • Learn graph embeddings and train prediction models
  • Formulate path prediction as a reinforcement learning problem
  • Integrate graph embeddings and train DQN or actor-critic agents
  • Develop sequence-to-sequence or transformer models for GPS trajectory alignment
  • Compare models to baselines
  • Experiment with graph-aware attention and constrained decoding
  • Design metrics and scenarios for accuracy, robustness, efficiency, and interpretability
  • Run ablations on embeddings and semantic attributes

Education

  • Currently in higher education

Languages

  • GermanAdvanced
  • EnglishAdvanced

Tools & Technologies

  • Python
  • PyTorch
  • TensorFlow
  • RDF
  • SPARQL

Benefits

Mentorship & Coaching

  • Comprehensive mentoring and onboarding

Learning & Development

  • Personal and professional development

Flexible Working

  • Flexible working hours
  • Mobile work

Other Benefits

  • Student apartments
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of BMW Group and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.

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