PHD RESEARCH ENGINEER - ACOUSTICS

We are looking for an experienced Research Engineer specializing in acoustics, audio signal processing, and Machine Learning to join an international Research & Development (R&D) project. In this role, you will be responsible for developing advanced audio signal processing algorithms and implementing Machine Learning models that run directly on embedded devices (On-device ML / TinyML). The project is delivered for an international client developing innovative solutions in the fields of acoustics and Edge AI. Obowiązki • Design and develop advanced audio signal processing algorithms. • Develop Digital Signal Processing (DSP) solutions for audio applications. • Design, train, and optimize Machine Learning and Deep Learning models for audio data. • Implement TinyML and Embedded AI models on resource-constrained embedded devices. • Develop embedded software in C/C++. • Build and optimize On-device Machine Learning solutions. • Collaborate with cross-functional R&D teams to develop next-generation audio technologies. • Contribute to projects involving acoustics, psychoacoustics, and audio signal analysis. Wymagania • PhD or PhD Candidate in Acoustics, Signal Processing, Electronics, Computer Science, or a related field. • At least 3 years of experience in applied Research & Development (R&D) projects. • Hands-on experience with Acoustics Audio: Signal Processing and Digital Signal Processing (DSP). • Strong proficiency in Python. • Good knowledge of Embedded C/C++. • Experience with Machine Learning and/or Deep Learning for audio applications. • Experience with TinyML, Embedded AI, or Edge AI. • Experience deploying Machine Learning models on microcontrollers. • Solid understanding of embedded systems and microcontroller-based development. • Knowledge of building acoustics, psychoacoustics, or acoustic standards and regulations will be considered an advantage. • English proficiency at B2/C1 level or higher. Oferujemy • B2B Contract cooperation • Rates: (37 - 50) EURO/hour + VAT • 100% remotely work