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Field
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—algorithms, interfaces and embodiment—through the pursuit of answers to a complex question: in what ways can we make life better for all with interactive digital-physical objects that channel their physical
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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modeling and numerical optimization techniques. Proficiency with programming languages such as Python, MATLAB, Julia, or C++. Experience developing and applying algorithms for simulation, optimization
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of Antwerp. See also: https://remotesensing.vito.be/news/sspirit-tackling-plastic-pollution The main task of the KU Leuven PhD project will be the further development and validation of a two versatile
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and Objectives Industry Objectives: Develop methods and algorithms for robust real-time 3D situational awareness and semantic 3D environmental segmentation. Create algorithms and representations
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solutions that assist in storage, investigation and dissemination of large data sets. Works with research team to develop new algorithms to support studies. Assists with reporting of methods, data and results
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD project aims to develop a
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psychological experiments, developing novel mathematics, inventing new algorithms, and making new philosophical arguments. Publish and share this research with the wider academic community. Help organize, once
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to continuous improvement and professional development, and to collaborate with personnel/departments across the University to facilitate student success.Salary Range: $45,000-62,000(Please note that the range
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | 1 day ago
, startups and patient partners. Your Mission as PhD is to develop novel machine-learning methods to (1) detect small, clinically meaningful changes in joints, (2) enable robust longitudinal monitoring and