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. The opportunity: We are looking for someone to analyse environmental soundscapes using signal processing or machine learning. Initially, you will work with underwater passive acoustic sound data, and later may
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aeroacoustics (wind tunnel testing, microphone arrays) MATLAB / Python for signal processing CFD software (ANSYS Fluent, OpenFOAM) FEM softwares (COMSOL, ACTRAN) Spectral analysis (FFT, wavelets) Behavioural
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Profile A PhD in (bio)acoustics, spatial ecology, marine environmental science, or a related subject Experienced in acoustic propagation modelling, signal processing, and data mining A strong background in
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(2024), pp. 1–55. [3] Fernando Gama et al. “Convolutional neural network architectures for signals supported on graphs”. In : IEEE Transactions on Signal Processing 67.4 (2018). [4] Luana Ruiz, Fernando
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Oldenburg Oldenburg, Niedersachsen | Germany | about 1 month ago
science, or a related subject Experienced in acoustic propagation modelling, signal processing, and data mining A strong background in programming, statistical analysis, and spatial modelling and mapping
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behavior and/or brain physiology. A strong analytic background, particularly in modeling neural systems and analyzing large datasets. Experience with acoustic signal processing, sound recognition, and
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fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements PhD degree in machine learning, automatic control, system identification, signal processing
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background in signal processing and time-series analysis; 6. English language skills sufficient to communicate and collaborate effectively in an international research environment Specific Requirements Desired
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embedded systems from vulnerabilities rooted in sensor physics, studying the impact of physical signals (e.g., acoustics, lasers, electromagnetic emissions) on AI and sensing systems, and innovating hardware
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Vibration Techniques Concepts, operation and maintenance of ultra-low vibration experiments, including control of mechanical, acoustic, cabling, vacuum-line, and cryogenic noise. • High-field Superconducting