Masterbeit Uncertainty-Aware Sensor Fusion Using Bayesian Neural Networks

Responsibilities

• Identify and understand relevant literature on Bayesian neural networks and sensor fusion.
• Integrate a Bayesian neural network component into an existing sensor fusion model.
• Run a benchmark with different sensor configurations to assess whether configuration uncertainty can be captured by the Bayesian component.

Qualifications

Studiengänge

• Computer Science
• Artificial Intelligence
• Robotics
• Math, Data Science or comparable degree program

Studienfokus

• Software development / programming
• Machine learning / deep learning
• Digital image processing
• Statistics / data science

Fachkenntnisse

• Solid understanding of popular machine learning and deep learning concepts
• Experience with statistical models
• Experience with 3D data processing and sensor data fusion is a bonus

IT-Kenntnisse

• Confident use of Microsoft Office, Git, and Linux (Ubuntu)
• In-depth knowledge of Python, C, or C++
• Proven experience with popular machine learning frameworks

Sprachkenntnisse

• English (fluent spoken and written)
• German is an advantage

Soft Skills

• High level of initiative
• Strong analytical skills
• Structured and independent way of working
• Ability to work in a team
• Goal-oriented