Mandatory Internship - Feature-based synthetic in-cabin data generation - REF74569M

Hey, you are looking for an exciting internship and would like to gain valuable insights into the field of Feature-based synthetic in-cabin data generation? Then we have just the thing for you!

We are looking for you starting as soon as possible for a 6-months internship, including at least 12 weeks in a mandatory internship to support us in our AI laboratory in Berlin. We will need you mostly on site in Berlin. But we also understand that there are days when you'd rather work from home. Therefore, together we find a solution that suits us all - remote working hours are therefore possible in consultation with your supervisor.

What can you expect from your internship:

• Literature review of existing feature augmentation methods for synthetic in-cabin data generation  
• Develop and implement feature augmentation methods
• Collaborate with cross-functional teams to identify and extract relevant features from raw data
• Assist in the creation and maintenance of data pipelines for efficient processing
• Contribute to the improvement of existing data generation models
• Participate in regular team meetings and present findings to stakeholders
• Document processes, methodologies, and results for future reference
• Support the evaluation and validation of generated synthetic data

Are you wondering whether you are suitable for the internship in the field of Feature-based synthetic in-cabin data generation? Here are key qualifications we are looking for:

• You study in the field of Computer Science, Machine Learning, AI, Computer Vision or comparable courses of study in a Master's program, so that you have basic aspects of our area of responsibility
• Strong programming skills in Python and PyTorch with demonstrable project experience are absolutely necessary in the context of this position
• You should have basic knowledge of GenAI concepts and their applications and a good understanding of neural networks and machine learning principles
• You have the ability to implement and validate novel research ideas independently
• Fluent English language skills in word and writing are absolutely necessary for us

In addition to these technical requirements, we are also looking for certain properties and skills:

• You are independent, goal-oriented and structured and know how to work effectively without losing track - always pay attention to high-quality results
• Analytical thinking and problem-solving kills are also beneficial and can help you solve the tasks effectively
• Creativity and flexibility are a matter of course for you and help you to find unconventional solutions
• A very good communication and teamwork skills are particularly important for us - after all, we always have to work together on solutions

Before you submit your application, there are a few things you should think about: We need your current certificate of enrollment, your current transcript of records and a confirmation from your university regarding the completion of a mandatory internship in order to be able to process your application.

If you are not from the EU area, please also send us your valid residence permit and your work permit including the additional sheet.

Applications from severely handicapped people are welcome.

• You will receive qualified support from our experienced specialists and PhDs to improve your professional knowledge and practical skills
• Your commitment to us is fairly remunerated: We know that your work is valuable and want to ensure that you are adequately remunerated
• We offer you flexible working hours with hybrid working models, where you have the opportunity to occasionally work from home, because we know how important the interaction of private and professional life is.
• Our location is centrally located in Berlin and we look forward to welcoming you to our Co-Working Space AI Campus
• We provide a powerful GPU infrastructure, because only with excellent technology can we achieve great
• Participate in journal clubs and networking events and share technical topics with your colleagues on campus

If you find yourself in our position and feel like working with us on exciting projects, then apply now and become part of our team!

Diversity, Inclusion & Belonging are important to us and make our company strong and successful. We offer equal opportunities to everyone - regardless of age, gender, nationality, cultural background, disability, religion, ideology or sexual orientation.

Ready to drive with Continental? Take the first step and fill in the online application.

Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent and affordable solutions for vehicles, machines, traffic and transportation. In 2023, Continental generated sales of 41.4 billion and currently employs around 200,000 people in 56 countries and markets.

The increasing level of automation in vehicles is shifting more and more driving tasks from the human driver to the car itself. Future vehicle interiors will have various driver and occupant monitoring sensors, which can provide intelligent in-vehicle HMI interactions such as automatic adjusting of in-vehicle control systems based on motion sickness detection, playing mood light or music based on emotion prediction, or ensuring automation level compliance based on driver activity recognition. We require a vast in-cabin driver dataset to deliver such sophisticated systems. However, collecting more data for in-cabin activity recognition is expensive. Therefore, synthetic data generation is an economical alternative. 

Due to advancements in large language models (LLM), Generative AI methods are widely used for synthetic data generation. However, such methods are computationally expensive, cannot generate diverse data, and are biased toward training data. This work aims to generate synthetic in-cabin data without additional computational cost using data augmentation methods in feature space.