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PET tracer, and their ongoing (pre)clinical translation, Groningen is taking the lead in imaging of Gram-positive infections. This PhD project will focus on expanding this initiative to the imaging
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or computer vision. A critical understanding of AI model development and evaluation, including the capabilities and limitations of generative AI and synthetic data. Experience with image analysis, synthetic
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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processing, machine learning, computational imaging, and clinical translation. Beyond your individual research contributions, you will serve as a technical coach for the PhD researchers, helping to align
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affects heat and mass transfer, and how surface design can improve the efficiency of the process. As a PhD candidate in the Thermal Conversion and Storage group at the University of Twente, you will
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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an image. Modern inverse freeform design methods compute surfaces that convert a given source light distribution to a desired target light distribution. These can be used to guide the design process for
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an individual ESA Member State or Associate Member under a bilateral partnership agreement concluded with ESA. As a result, a representative of the sponsoring State participates in the selection process. In
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(adaptive) imaging strategies and reconstruction. The research combines ultrasound physics, signal processing, machine learning, computational imaging, and clinical translation. Beyond your individual
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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental