Internship / Master's Thesis Generative AI for Autonomous Driving (f / m/d)
Wolfsburg, Germany
Key offer highlights
Backend: Java / .NET / Node / Python
Employment: contract
Full-time
Description
Generative AI, Machine Learning, Autonomous Driving, Automated Driving, Anomalies, Deep Learning, Scene Understanding Der Bruttostundenlohn für Praktika (auch Pflichtpraktika) und Abschlussarbeiten entspricht der Höhe des aktuellen Mindestlohns. Contact person for this posting: Hartmut Fromm Generative AI, Machine Learning, Autonomous Driving, Automated Driving, Anomalies, Deep Learning, Scene Understanding
Company
Volkswagen AG
Contract
Fixed-term
Work Environment
As part of Volkswagen Group Innovation, our team deals with AI & Data Analytics tasks in the development of digital services for different Volkswagen Groupbrands. This includes topics such as processing and analyzing vehicle data as well as integrating artificial intelligence (AI) into digitized vehicles. State-of-the-artAI methods address perception and scene understanding problems in automated driving. We investigate the effect of difficult and adverse driving scenarios aspart of testing processes. Within these fields of innovation, we offer you the possibility to participate in the research and development of intelligent algorithms inan interdisciplinary and to help shape the mobility of tomorrow. During your internship (at least 6 months) or thesis work, you will have the chance to tackle acomplex issue in the exciting field of generative AI and automated driving. If you are pursuing a master’s thesis, the task and research questions will bedetermined together with your professor upon confirmation of supervision.
Department
Research and Development
Shift
Full-time
Experience
Interns
Qualification requirements
Master’s student in Computer Science, Robotics, Data Science, Mathematics, Physics, Engineering Sciences or a related qualification
Very good to good academic achievements
Strong analytical and conceptual skills, familiarity with scientific methods
Ability to work independently and in multidisciplinary teams, highly motivated
Good knowledge of an object-oriented programming language, preferably Python, and of deep learning methods
Profound experience with deep learning libraries like PyTorch in the context of research projects
Ideally practical experience in the area of driver’s assistance systems or automated driving
Fluent in English (at least language level B2)
Possible Tasks within this Role
Development and implementation of concepts to systematically generate traffic scenarios with anomalies or adverse conditions
Research and analysis of current literature on the generation of anomalous data
Practical investigations of data-driven deep learning methods for scenario generation for a selected use case
Evaluation of the quality of the generated data according to self-developed or predefined criteria
Documentation and presentation of the results
The following documents must be submitted with the application
Cover letter and CV
Current certificate of enrolment
Current transcript of records
In the case of a compulsory internship, an additional certificate from the university
Work permit for non-EU citizens