Master Thesis (m/f/d) Structural Pattern Recognition for Operating User Vehicle Interfaces
Porsche AG

Master Thesis (m/f/d) Structural Pattern Recognition for Operating User Vehicle Interfaces

Porsche AG
  • Graduate Program / Job Rotation Program (From 19 to 24 months)
  • Weissach (Germany)
  • Published on August 29 2021
Aufgaben

Join our expert team of engineers and researchers to work on the future of automotive user interfaces. You will take on responsibility in an exciting project from day 1 and be able to contribute your ideas while getting to know the Porsche spirit.

Motivation

For the next generation of automotive user interface systems, it will be essential to have a profound understanding of the user interface display and operating behavior. Information we can gain through sensors & external APIs are the enabler for an optimized user interface, hence a more performant driver experience. One factor is being able to recognize display and control patterns under dynamic conditions, thus real-life environments.

Objective

The master thesis aims for an automated solution to recognize operating patterns for classified display & control sequences on a large naturalistic driving data set of vehicle bus information.

The exact structure of the thesis will be defined with the thesis student and the university.

Tasks
  • Research on the state of science in the area of Deep Learning (LSTM, CNN architectures), Time Series Classification, Representation Learning
  • Appropriate feature engineering and sensor fusion of multivariate time streams
  • Fuse high-dimensional multivariate time series data ranging from continuous, categorical and textual input variables
  • Implementation of state-of-the-art machine learning models
  • Cleaning of data, visualization and processing of results
  • Analysis of existing algorithms regarding statistical efficiency, technological feasibility and prediction quality
  • Analysis of applied algorithms under human-computer interaction aspects


Start: as of now

Duration: 6 months

Anforderungen
  • Studies in engineering or natural sciences (e.g. computer science, mathematics, physics, electrical engineering, etc.), ideally with a focus on machine learning, data science, information technology, quantitative methods
  • Qualified knowledge in the field of Machine Learning (e.g. with Python, CNN) and experience in dealing with large data sets
  • Very good programming skills (C/C++, Python, etc.)
  • Ideally, first experience with a deep learning framework, e.g. TensorFlow or PyTorch
  • Ideally experience with implementing prototypical ML and (mobile) UI applications in practice (for example with tensorflow.js)
  • Very good written and spoken English
  • Passion to learn and apply new programming languages and technology concepts
  • Analytical thinking, structured and independent way of working, creativity and the motivation to grow with challenges


Unternehmensprofil

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