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affected by warping, addressing both audio analysis and synthesis tasks. The methodological scope spans stochastic signal processing and machine learning, including hybrid physics‑guided and data‑driven
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quantitative methods to analyze ESM data, including time series analysis and multilevel modeling techniques. Evaluate the validity and psychometric properties of ESM items assessing amotivation using qualitative
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visualization systems. Research themes: The PhD student will contribute to several of the following topics: Computer-generated holography (CGH); Optical system analysis and simulation; Developing AI/ML algorithms
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attention to quality, integrity, creativity and cooperation. You have a strong background in signal processing, with emphasis on acoustics, array processing, or time–frequency analysis. You are eager to learn
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societal demand in the field of applied life sciences, such as cleantech and environmental technology, for instance. In 2015, prof. Siegfried Vlaeminck launched Biobased Cleantech and Environmental Analysis
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topics Crystallization of polymers Analysis of the structure of semi-crystalline polymers Mechanical and thermal properties The work involves lab experiments, data acquisition, validating findings