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includes the design and manufacturing of miniaturized platforms and their optimization for biochemical assays and analytical procedures. For a third-party funded project, running for four years, we
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vibration, strain, and environmental sensors with MCU-class edge AI capabilities. Optimize sensing front-ends, power management, and communication interfaces for minimal standby and inference energy. On-chip
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species annotations, climate, and topography, into deep learning algorithms. Test deep learning models (Transformers and CNNs) for optimal accuracy using large datasets that include over 110,000 tree
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, you will design, prototype, and optimize advanced simulation algorithms—particularly in the domain of cloth and deformable materials and contribute to our next generation of rendering and learning-based
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, investigations and optimization of hydrogen production via methane pyrolysis for decarbonization of industrial high-temperature processes with potential for negative carbon emissions. Your tasks Setup
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(LLE), and diffusion coefficients—key data for designing and optimizing chemical processes. Because conventional experiments are often time- and resource-intensive, particularly for multicomponent
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interdisciplinary team of researchers with expertise in thermodynamics, process design, energy system optimization, and life cycle assessment, working collaboratively with research and industry partners. You will
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integrating various datasets, such as tree species annotations, climate, and topography, into deep learning algorithms. Test deep learning models (Transformers and CNNs) for optimal accuracy using large
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, Human-Robot Interaction, Imaging Technology, Machine Learning, Medical Informatics, Medical Robotics, Natural Language Processing, Neuroinformatics, Optimization, Perceptual Inference, Probabilistic
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and drug testing You will have a dual role in setting up and culturing the 3D skin models and optimizing sensor technology (e.g. TEER and TEWL) to enable a robust assessment of skin barrier