Population genomics of freshwater sardines in Central African lakes, and its translation into fisheries policy Hasselt University
Implementation of breathomics in health and disease. University of Antwerp
Statistical methods for studying and monitoring biological and industrial processes Ghent University
Advances in sensor and computing technology are continuously making the acquisition and storage of data more efficient. Statistical modelling and analysis can be used to extract useful insights from data, but are often accompanied with several challenges. In this project, we will develop statistical methods that are generic applicable to study and monitor biological & industrial processes .
Whaleboats in the Forest: Subaltern Technologies of Transportation on Congo’s Inland Waterways KU Leuven
Congo’s wooden baleinières (Fr. whaleboats) are locally developed and crafted socio-technical assemblages that account for up to 50% of all transportation of goods and people on the waterways of the Congo Basin. Despite the vital role of these subaltern technologies of transportation for the livelihoods of millions, the socio-technical complexities responsible for their success have never been studied. Rooted in older boat building traditions ...
Micro/nano-electromechanical system (M/NEMS) resonant mass sensors have attracted utmost interest over the past two decades. This is due to their wide range of applications, especially in biochemistry, for instance weighing single molecules, nanoparticles, and even monitoring the growth of living cells. However, their performance is significantly decreased when operated at ambient air and measurements take a considerable time. Therefore, ...
A probabilistic programming approach to the analysis of high-dimensional biological monitoring data. Ghent University
Plant phenotyping studies or studies that monitor of animal or human behavior often rely on the collection and analysis of high-dimensional and (spatio-) temporal datasets. In this research project, probabilistic programming approaches will be developed that allow to incorporate prior knowledge on the study objects (e.g., shape or behavior) into the data analysis pipeline to make the analysis more robust.