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renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks
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knowledge of Microsoft Word, Excel and PowerPoint. You have experience in, or are willing to learn MATLAB. You hold the FELASA B certificate, or international equivalent or you are willing to follow a
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precise gradients in mechanical forces, temperature, and biochemical cues within 2D and 3D culture conditions. Mechanics Analysis: Investigate the effects of these controlled environments on cellular
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military performance, presenteeism, and may even lead to costly evacuations during deployments. This PhD project builds upon pioneering research at MHQA and aims to implement and evaluate allergy screening
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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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network analysis.•experience with historical and/or theological research.•willingness to engage with interdisciplinary approaches and theoretical frameworks.•work independently, possess organisational
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impedance analysis; optical and thermal measurement principles are also being considered. The results obtained with the sensor are compared with the results of analytical reference techniques such as
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environment Bonus but not required Experience in single-cell and spatial omics data analysis Experience with highly multiplexed flow cytometry Background in immunology The opportunity to work on high-impact
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or 50 years however they live with increased pulmonary vascular resistance and are prone to various forms of vascular shunting. In this project the student will perform proteomics analysis of patient