Research Assistant (E13 TV-L) at Institut für Bildung in ...

Intro

The position involves researching methods for testing and validating deep neural networks in the context of autonomous driving, with a focus on safety and monitoring.

Tasks

Independently researches methods for testing and validating deep neural networks in the context of autonomous driving.
Develops methods for online monitoring and retrieval of corner cases in road scenes that could potentially pose a danger to an autonomously driven vehicle.
Conducts numerical experiments with deep learning frameworks such as PyTorch or TensorFlow for online monitoring of perception networks and evaluates the results statistically.
Investigates experimental designs for ensuring the safety of neural networks under variable lighting conditions and in teacher-student configurations and implements these findings in numerical experiments.
Writes scientific papers on the topic of the 'SafeAIEngineering' project.
Participates in the activities of the SafeAIEngineering consortium as part of the project.
Maintains the exchange with the industrial partners and other participants in the consortium and takes on project management tasks.

Requirements

Successfully completed academic university degree (Master, Diploma or equivalent) in Mathematics.
Programming experience, preferably in Python.
Programming experience with deep learning frameworks such as PyTorch or TensorFlow and cluster computing.
Knowledge of statistical learning theory.
Good knowledge of German and/or English required; willingness to acquire the respective missing language skills.

Benefits

Part-time employment may be possible; subject to funding approval being granted.

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