Predictive Process Monitoring with Graph Neural Networks

vor 2 Wochen


Nürnberg, Bayern, Deutschland Fraunhofer-Institut für Integrierte Schaltungen IIS Vollzeit
Join Our Research Team

We are seeking a highly motivated student to collaborate with our Process Intelligence team at Fraunhofer-Institut für Integrierte Schaltungen IIS. As a research assistant, you will work on a Master's/Bachelor's thesis project focused on Predictive Process Monitoring with Graph Neural Networks.

About the Project

Our team analyzes, designs, and optimizes data-driven processes using Machine Learning methods. We are looking for a student who is interested in combining research and practice and wants to develop further in the field of Machine Learning and Process Mining.

Responsibilities
  • Research the latest methods in Process Mining, Predictive Process Monitoring, and Graph Learning
  • Investigate and implement various Graph Neural Networks for Predictive Process Monitoring use cases
  • Compare, interpret, and evaluate the achieved results with each other and with traditional approaches
  • Prepare findings in engaging presentations for the team
  • Expand our existing software inventory with selected approaches
Requirements
  • Currently studying Computer Science, Mathematics, Data Science, or a related field
  • Experience in Python (especially ML frameworks like PyTorch, sklearn, etc.)
  • Interest in Machine Learning (especially Graph Learning) and willingness to apply this interest to challenging tasks
  • Initiative and independent way of working
  • Excellent English skills (German skills are a bonus)
  • Advantageous: Experience with PyTorch Geometric and basic understanding of Process Mining
What We Offer
  • Flexible working hours
  • Open and friendly team work
  • Varied tasks with room for creativity
  • Exciting seminars and events
  • Networking with scientists
  • Active contribution in applied research
  • Interesting and innovative projects

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity.

Please apply online with your cover letter, CV, and transcripts. We look forward to getting to know you.



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