Master Thesis

The future is looking for people to take it to the streets. Interested?

**Master Thesis (M/F/d): Context-Aware In-Car Recommender System: Predicting UI Interactions (User Needs) with Driving Context**:

- **Code number**:J000001854
- **Entry level**:Thesis
- **Location**:Weissach
- **Organization**:Dr. Ing. h.c. F. Porsche AG
**Tasks

**Tasks***

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 (UI) 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 predict the next UI interaction based on the driving context.

**Objective**

The master thesis aims for a recommender system that recognizes 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 supervisor.

**Tasks**
- Research on the state of the art in the area of Deep Learning (LSTM, CNN architectures), Time Series Classification and Prediction, Representation Learning for detecting user interaction patterns, and Recommender Systems
- Exploratory and predictive ML model for structural user interaction pattern recognition
- Appropriate feature engineering and fusing high-dimensional multivariate time series data ranging from continuous, categorical and textual input variables
- Model evaluation regarding statistical efficiency, technological feasibility and prediction quality
- Analysis of applied algorithms under human-computer interaction aspects

**Start**: February/March 2023

**Duration**:6 months
**Qualifications

**Qualifications***
- 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 in Python
- experience with at least one deep learning framework, e.g. TensorFlow or PyTorch
- Very good written and spoken English
- Analytical thinking, structured and independent way of working, creativity and the motivation to grow with challenges
**At a Glance

**At a Glance***

“In the beginning, I looked around and could not find quite the car I dreamed of. So I decided to build it myself.”

This quote from Ferdinand Porsche sums up what Porsche is as a brand, as a company, as a car manufacturer and as an employer. The “Porsche idea” has produced unique sports cars, such as the Porsche 356 and the 911. With the combination of tradition, innovation and our employees' Porsche typical - sometimes unconventional - ways of thinking, we make automobile dreams come true and always have that “little bit more” in our sights. But Porsche is more than “just” an exclusive sports car producer. Because Porsche has a lot to offer as an employer as well: numerous entry and career opportunities, measures for combining work and family, and flexible working hours.
**Exclusive look behind the scenes

**Exclusive look behind the scenes***

Regardless of what others do, we are always striving to redefine our limits and set standards. But all of this can only be achieved today and in the future with employees and management who always have an eye for more than the standard. What does that look like? Get to know your future colleagues.

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**How to apply?

**How to apply?*