Master Thesis Worker, Sound Experiences Lab

Dolby Laboratories; Nürnberg; Vor Ort; EUR 40.000 - 60.000; Teilzeit

Zusammenfassung

A leading audio technology company in Nürnberg is seeking a Master’s student for a thesis project in audio quality prediction. The role involves conducting literature reviews, prototyping ideas, and implementing machine learning models. Ideal candidates will have strong knowledge in machine learning and a genuine interest in audio technologies, with familiarity in frameworks like TensorFlow or PyTorch.

Qualifikationen

• Currently enrolled in a Master’s program in a relevant technical field.
• Strong knowledge of machine learning and deep learning concepts.
• Familiarity with neural network frameworks.

Aufgaben

• Conduct a literature review on related research.
• Reproduce and extend existing research approaches.
• Propose and prototype new ideas.

Kenntnisse

Machine learning

Deep learning

TensorFlow

PyTorch

Statistical analysis

Ausbildung

Master’s program in Computer Science

Master’s in Machine Learning

Master’s in Electrical Engineering

Jobbeschreibung

Summary

Dolby’s Sound Experiences Lab in Nürnberg specializes in audio codecs and their sonic quality evaluation. We apply modern deep learning techniques to advance the state of the art in audio coding performance and develop systems to evaluate audio quality. We are passionate about exploring and building new possibilities enabled by emerging technologies.

This thesis project will focus on exploring and developing a novel approach for predicting audio quality by leveraging latest tools and methodologies.

Responsibilities

• Conduct a literature review on related research.
• Reproduce and extend existing research approaches.
• Propose and prototype new ideas.
• Assist in the collection and processing of datasets.
• Implement, train, and evaluate machine learning models.

Requirements

• Currently enrolled in a Master’s program in Computer Science, Machine Learning, Statistics, Electrical Engineering, or a related technical field.
• Strong knowledge of machine learning and deep learning concepts.
• Familiarity with one or more neural network frameworks (e.g., TensorFlow, PyTorch).
• Genuine interest in audio and / or media, with awareness of AI-related developments and trends.