Student Assistant Artificial Intelligence

**Future. Discover. Together.**
Excellent research and innovation are at the centre of the work of the HHI - Fraunhofer Institute for Telecommunications. We are a world leader in researching mobile and optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation

**What you will do**
- Use of XAI tools to explain machine learning models
- Implementation of deep learning
- Improvement of models, e.g. in terms of efficiency, training performance or inference behavior

We promise you excellent contacts in the relevant industrial and scientific environment. We offer a wide range of opportunities in an international environment. We are looking for people who want to make a difference. Make something out of it

In our video you will find information about our student assistants and their work.

**What you bring to the table**
- Enrolled Bachelor's/Master's student in full-time studies in the fields of computer science, mathematics, physics, electrical engineering or related courses with good to very good grades
- Programming experience, especially good to very good knowledge of Python
- Experience with machine learning, in particular with neural networks and their implementation (Pytorch, Tensorflow or similar)
- Motivation and Initiative
- Interest in explainable artificial intelligence (XAI) and/or applied machine learning (AML) and/or efficient deep learning (EDL)

When applying, it is mandatory to indicate and justify a preference of the following available fields of work and topics (i.e. **AML, EDL or XAI**):

- **Applied Machine Learning (AML)**:

- Multimodal Machine Learning
- Graph Neural Networks
- Time series analysis
- Diffusion models
- Large Language Models
- Applications in health and medicine-related topics, e.g. medical text, tabular data and image processing, infection prediction, quality control.
- Applications in climate-related topics, e.g. nowcasting, downscaling, prediction of extreme weather events
- **Efficient machine learning (EDL)**:

- Efficient distributed learning
- AI model coding and compression
- Optimization of neural networks for energy efficiency and hardware adaptation
- **Explainable Artificial Intelligence (XAI)**:

- Fundamental research and method development in areas of Local Feature Attribution, Global and Mechanistic Interpretability
- XAI-based model improvements
- XAI Evaluation and XAI-based AI model evaluation
- XAI in Physics-Informed Neural Networks (PINNs)
- Applications in a wide range of machine learning models, architectures, inference targets and data modalities.

The position requires physical presence in Berlin.

**What you can expect**
- Attractive salary
- Modern and well-equipped workplace in a central location
- Good and cooperative working atmosphere in an international team
- Flexible working hours
- Opportunities to write a Master's or Bachelor's thesis, often in close cooperation with industry partners
- Opportunities for home office

The position is initially limited to 1 year. An extension is explicitly desired.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

If you need information about this position, please contact us:
Herrn Prof. Dr. Wojciech Samek

Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute HHI

Requisition Number: 77383 Application Deadline: 02/15/2025