This is an internship program for international Undergraduate and Graduate students of Computer Science and related fields. During their internship, students will have the opportunity to get hands-on experience with HCI research in an internationally leading lab. They will be closely guided by members of the team in working on trending topics in interactive technologies and learn the methods that underlie technical HCI research.
The program targets Master’s students and advanced undergraduate students (starting after the end of year two).
The internship will be in-person, at Saarland University in Saarbruecken, Germany. The typical duration is 4-6 months. Only in exceptional cases, we may consider shorter internships of min. 2.5 to 3 months; in this case, the student is expected to familiarise themselves with relevant provided project materials before joining.
Travel (return ticket, economy class) and accommodation for the duration of the internship will be covered by the lab.
Program dates: The 2025 program runs between May 1 to Sept 1, 2025.
Online application: Interested candidates may fill up this form. You will need to upload your transcripts, resume, and a personal statement detailing your motivation for applying, how the program would help your future goals, and explaining your project preferences based on your skills and prior experiences. Further details can be found in the form.
Application deadline: Applications must be submitted by 11:59 PM CET, on Monday February 15, 2025.
Shortlisted candidates will be contacted by email for interviews.
Project 1 – Embroidering shape-changing textiles
Field of study: Fabrication, shape change, textiles, graphics
Description: This project looks into enabling output capabilities on the human body but with a soft, flexible, and integrated form factor based on textiles. We plan to do this via digital embroidery machines, which perform programmed stitches on a base fabric based on a vector design file. They can create custom, entirely fabric-based textile patterns and have a relatively straightforward fabrication workflow. Exploiting these benefits, this project wants to explore how to create 3D shapes and shape changes from traditionally planar embroideries.
Nature of student involvement: It’s flexible and up to discussion as to which part of the project the student wants to be more involved in. These could include developing and extending the fabrication approaches, creating a design tool for customization, and computationally modeling the shape-changing structures
Skills we are interested in: Prototyping and fabrication experiences, especially textile or compliant material ones
Modeling (Fusion, Rhino, etc.) and graphics
Contact: yjiang@cs.uni-saarland.de
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Project 2 – Intelligent Situated Guidance with AR
Field of study: AR/VR, Multimodal Large Language Models
Description: The advances in multimodal LLMs allow us to infer different kinds of information about a user and their context. Meanwhile, wearable augmented reality (AR) devices provide a rich, immersive canvas to enhance the user’s experience through situated visual feedback. This project seeks to combine the power of multimodal AI and AR to develop a new class of interactive systems that can infer users’ context and provide just-in-time guidance seamlessly.
Nature of student involvement: Students will work on the development of LLMs and/or develop AR/VR applications on Unity that are relevant to the project.
Skills we are interested in:
- Experience with Unity and strong programming skills in C# (or)
- Programming and development skills in Python (frameworks like PyTorch or TensorFlow),
- Experience with integrating and fine-tuning LLM and CV models into interactive systems
Contact: ram@cs.uni-saarland.de
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Project 3 – Intelligent Control of Supernumerary Robotic Limbs with GenAI
Field of study: Human Robot Interaction (HRI), Generative AI
Description: Supernumerary robotic limbs (SRLs) present an opportunity to enhance human capabilities by providing extra arms or hands that operate in coordination with the user. Recent advances in generative AI enable more intuitive and adaptive control mechanisms, allowing SRLs to predict user intent, refine motion patterns, and seamlessly assist in tasks. This project aims to leverage generative AI techniques, to enhance the intelligence and usability of SRLs in real-world applications.
Nature of student involvement: Students will contribute to the development of SOTA (state of the art) generative AI models for interaction with SRLs.
Skills we are interested in:
- Understanding of human-robot interaction and intent recognition
- Strong programming skills in Python and/or C++
- Knowledge of machine learning frameworks like PyTorch or TensorFlow
- Familiarity with generative AI models (e.g., diffusion models, transformers)
Contact: saberpour@cs.uni-saarland.de
