Aktuelle Jobs im Zusammenhang mit Master Thesis Causal Discovery for Vehicle Quality Data using Deep Learning Models - Munich, Bayern - BMW Group


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Master Thesis Causal Discovery for Vehicle Quality Data using Deep Learning Models

vor 1 Monat


Munich, Bayern, Deutschland BMW Group Vollzeit
Job Description

As a master student in computer science or a related field, you will have the opportunity to work on a cutting-edge research project focused on causal discovery for vehicle quality data using transformer models. This project aims to leverage the power of attention-based deep learning models to interpret data and draw causal graphs, explaining the relationships between variables.

Key Responsibilities
  • Engage in state-of-the-art research on transformer models for causal discovery
  • Work with real-world datasets to draw applicable conclusions
  • Push the boundaries of predictive maintenance using deep learning approaches
  • Gain practical AI experience by implementing PyTorch and Hugging face models
  • Utilize our cutting-edge training infrastructure and platforms to conduct experiments and evaluate your approach efficiently
  • Present the thesis orally and through a research paper
Requirements
  • Strong knowledge in deep learning, transformers, graphs, and NLP
  • Excellent programming skills in Python, PyTorch, and experience with modern cloud environment tools such as AWS
  • Fluency in English
  • Driven by curiosity and motivated to solve scientific problems independently as well as sharing ideas and working in a team
What We Offer
  • Comprehensive mentoring & onboarding
  • Personal & professional development
  • Flexible working hours
  • Digital offers & mobile working
  • Attractive remuneration
  • Apartment offers for students (subject to availability & only Munich)
  • And many other benefits

We are committed to diversity and inclusion in all its dimensions and see it as a strength for our teams. Equal opportunities are a particular concern for us, and the equal treatment of applicants and employees is a fundamental principle of our corporate policy.