Student Assistants (w/m/d) – Quantum Computing / Quantum Circuit Compilation - #943506
Fraunhofer IIS
Datum: vor 10 Stunden
Stadt: Nürnberg, BY
Vertragstyp: Ganztags

The Fraunhofer-Gesellschaft ( www.fraunhofer.com ) currently operates 76 institutes and research institutions throughout Germany and is the world’s leading applied research organization. Around 30 800 employees work with an annual research budget of 3 billion euros.
The »Self-Learning Systems« group at Fraunhofer IIS is part of the »Precise Positioning and Analytics« department and located at the institute’s Nuremberg site. Our team members have diverse academic backgrounds from computer science and engineering to physics. We combine expertise in a range of advanced machine learning (ML) topics. One of our research goals is to provide robust and safe algorithmic solutions for control and decision-making tasks for systems in complex dynamic environments. To this end, we employ deep learning in combination with reinforcement-learning techniques. We research dependable reinforcement learning, i.e., we want to learn behaviors that are safe, performant, and explainable for many different tasks. There is a lot to learn and develop on the way and we are eager to hear about your ideas.
What You Will Do
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity.
Haben wir Dein Interesse geweckt?
Interested?
Apply online now (PDF: cover letter, CV, transcripts). We look forward to getting to know you!
Fraunhofer-Institute for Integrated Circuits IIS
www.iis.fraunhofer.de/en
The »Self-Learning Systems« group at Fraunhofer IIS is part of the »Precise Positioning and Analytics« department and located at the institute’s Nuremberg site. Our team members have diverse academic backgrounds from computer science and engineering to physics. We combine expertise in a range of advanced machine learning (ML) topics. One of our research goals is to provide robust and safe algorithmic solutions for control and decision-making tasks for systems in complex dynamic environments. To this end, we employ deep learning in combination with reinforcement-learning techniques. We research dependable reinforcement learning, i.e., we want to learn behaviors that are safe, performant, and explainable for many different tasks. There is a lot to learn and develop on the way and we are eager to hear about your ideas.
What You Will Do
- You work on topics related to quantum circuit compilation
- You will update our literature overview on the state of the art in both RL-based quantum circuit compilation and LLMs and translations as applied to quantum computing
- You operate quantum computing frameworks like Qiskit
- You use existing and emerging quantum hardware in the Munich Quantum Valley
- You study in a physics, mathematics or computer science program
- You are familiar with at least one of these topics: auto-encoders, transformers, reinforcement learning or graph neural networks
- You have first experience in python programming and libraries like PyTorch, TensorFlow, NumPy and PyTorch geometric
- You are familiar with the topic of quantum computing and have experience with libraries like Qiskit
- You speak English fluently
- Flexible working hours
- Open and friendly teamwork
- Varied tasks with room for creativity
- Exciting seminars and events
- Networking with scientists
- Active contribution in applied research
- Interesting and innovative projects
- Mentoring program » josephine « for talented female students
We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity.
Haben wir Dein Interesse geweckt?
Interested?
Apply online now (PDF: cover letter, CV, transcripts). We look forward to getting to know you!
Fraunhofer-Institute for Integrated Circuits IIS
www.iis.fraunhofer.de/en
Wie bewerbe ich mich?
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