Internship Neural Architecture Search Reinforcement Learning (f/m/d)

Environment

As part of Volkswagen Group Innovation, the AI & Data Analytics subdivision deals with the methodology and concept development of digital services for all Volkswagen Group brands. The main topics are, on the one hand, the processing and analysis of vehicle data and, on the other hand, the integration of artificial intelligence (AI) into digitized and networked vehicles. With the help of AI, for example, aging information and misbehavior of vehicle components are detected, but also perception tasks of autonomous driving are solved. Within these areas of responsibility, we offer you the opportunity to participate in the research and development of intelligent algorithms in a young and interdisciplinary team and to help shape the mobility of tomorrow.

Possible tasks within this role

• Advise and support you in implementing advanced machine learning models

• Optimization with the help of artificial intelligence, with a focus on the development of deep reinforcement learning models for automated driving applications

• Optimize hyperparameters and network architectures using various optimization algorithms

• Explore and compare different modeling approaches to improve performance and automate optimization processes

• Solve complex mathematical problems, formulate and present hypotheses to influence solution design

Qualification requirements

• Students of Data Science, Computer Science, Computational Science, Mathematics or a comparable field of study

• Proof of good programming skills (e.g. in Python, C#)

• Hands-on experience in the field of machine learning (ML)

• Hands-on experience in developing ML and optimization algorithms

• Experience in reinforcement learning is an advantage Basic-knowledge of Unity3D's simulation software is an advantage

• Ability to work independently on a scientific topic

• German and/or English level B2

The following documents must be submitted with the application

• ​​​​Curriculum Vitae

• Current certificate of enrolment

• Current transcript of records

• In case of a compulsory internship, a certificate from the university

• Work permit for non-EU citizens

Contact person for this posting: Brigitte Adam-Huth