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Working Student – Machine Learning for Audio Compression (all genders)

Fraunhofer IISvor 10 StundenWerkstudent
Vor OrtEnglisch erforderlichTechKI, ML & Data Science

Erforderliche Skills

LinuxNeural NetworksGitEvaluation PipelinesFFTPythonSpectrogramsAudio CompressionDeep LearningTraining PipelinesSignal Processing

Stellenbeschreibung

Fraunhofer IIS hat diese Stelle ausgeschrieben. Unten erklären wir, was sie für dich als Werkstudent:in in Erlangen bedeutet: deine Wochenstunden, dein Netto und deine Visumsgrenzen. Du kannst außerdem ChatGPT oder Claude mit einem fertigen Prompt öffnen, um deinen Lebenslauf anzupassen, deine Eignung zu prüfen, ein Anschreiben zu verfassen oder dich auf das Interview vorzubereiten.

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Beschreibung bereitgestellt von Fraunhofer IIS

Welcome to Fraunhofer Institute for Integrated Circuits IIS!

As the largest institute within the Fraunhofer-Gesellschaft, we have been conducting research for over 30 years in diverse fields such as artificial intelligence, microelectronics, sensor systems, data collection, signal processing and transmission. Talents from various engineering and natural science disciplines will find a wide range of exciting research topics under a single roof. A few highlights that reflect our innovative strength: Neuromorphic computing, 5G/6G mobile communication technologies, generative AI in speech and signal processing, and X-ray imaging for e-mobility. And that’s just the beginning! Which sustainable solutions will you find with us?

You are interested in advancing your skills in Machine Learning while working on audio processing and compression technologies?

Then have a look at our offer!

Be part of change

The department AME-A develops innovative codecs for the transmission of audio signals. Our solutions are suitable for a wide range of signals—from speech and music to immersive 3D audio—across a broad spectrum of bitrates and are already being successfully used by major providers in the streaming and broadcast industries.

  • Machine Learning: You implement neural network components and architectures, develop training and evaluation pipelines, and analyze model performance to continuously improve results.
  • Audio & Data Processing: You create and prepare training datasets, process audio data using signal processing techniques, and support the design and evaluation of listening tests.
  • Development & Optimization: You contribute to the development of AI-based audio compression solutions by training and evaluating models, optimizing workflows, and improving model performance.

What you contribute

  • You are currently studying Computer Science, Electrical Engineering, Data Science, Artificial Intelligence or a related field.
  • You have a basic understanding of Machine Learning / Deep Learning and are familiar with signal processing concepts and audio data (e.g., sampling rate, FFT, spectrograms).
  • You have strong programming skills in Python and enjoy implementing and experimenting with machine learning models.
  • You are familiar with Git and have basic experience working in a Linux environment.
  • You are interested in audio compression and motivated to contribute to innovative AI-based research and development projects.

What we offer

  • Organize your schedule: Benefit from flexible working hours that are perfectly compatible with your studies.
  • Become part of a creative team: Experience an open and friendly working atmosphere in which your ideas are valued.
  • Variety that inspires: Look forward to divers tasks that inspire and challenge you.
  • Shape the future with us: Take part in application-oriented research and put your theoretical knowledge to practice.
  • Innovation that inspires: Exciting and pioneering projects that make a real difference.

We will agree your start date and weekly working hours with you individually (as a working student 8 to 20 hours per week for at least one semester). You can reduce your hours before exams and increase them during semester breaks. We are looking for someone interested in a long-term collaboration, and please note: the position is on-site only. You can set your working days flexibly. After your studies, there are attractive opportunities to join the institute on a full-time or part-time basis. You can flexibly determine the working days of your fixed-term employment contract.

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. Severely disabled people are given preference if they are equally qualified.

About Fraunhofer

The Fraunhofer-Gesellschaft is one of the world’s leading applied research organizations. 75 institutes develop cutting-edge technologies for our economy and society – more precisely: 32 000 people working in technology, science, administration and IT. They know: If you join Fraunhofer, then you are able to promote change. For themselves, for us and for the markets of today and tomorrow.

Ready for change?

Then apply now and make the difference! (PDF: Cover Letter, Resume, Certificates).

Do you have questions about the application process? Our recruiter Svenja Hofmann will be happy to assist you.

E-Mail Address: [email protected]

Location: Erlangen

Wichtiges für Werkstudierende

Was diese Werkstudentenstelle im Bereich Tech in Erlangen für dich bedeutet: die Wochenstundenregeln, die Vorteile bei den Sozialabgaben und worauf internationale Studierende vor der Bewerbung achten sollten.

Wochenstunden

Werkstudierende dürfen während des Semesters bis zu 20 Stunden pro Woche arbeiten, in den Semesterferien Vollzeit. Wer das einhält, behält den Studierendenstatus und die Werkstudentenvorteile.

Werkstudenten-Regeln

Sozialabgaben

Dank des Werkstudentenprivilegs zahlst du keine Beiträge zur Kranken-, Pflege- und Arbeitslosenversicherung — nur die Rentenversicherung greift. Dir bleibt mehr netto als in einem regulären Job.

Versicherung prüfen

Internationale Studierende

Studierende von außerhalb der EU dürfen 140 volle oder 280 halbe Tage im Jahr arbeiten (seit März 2024, zuvor 120/240). Ein Werkstudentenvertrag passt meist in diesen Rahmen — prüfe die genauen Grenzen auf deinem Aufenthaltstitel.

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