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at higher risk offered PSA blood tests which are not definitive. Our research aims to develop an image-based approach to screening, combining PSA testing with MRI to better identify aggressive cancers
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reputation for carefully designed and precisely controlled experiments, high quality temporally and spatially resolved field experiments using particle image velocimetry combined with synchronised measurements
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resonance energy transfer, siRNA mediated gene knock out, cellular imaging, qPCR, etc.) to elucidate unknown interactions between GPCRs and receptor tyrosine kinases at the cellular level. Analyses will focus
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for imaging plant tissues (rose cuttings) Realisation of a corresponding measuring stand and implementation of test series for imaging Realisation of a data processing routine for the automated detection
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interpret thermal images with researchers and receive retrofit advice from professionals, the project aims to also improve the ability of households to take action. By addressing barriers to retrofitting and
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diagnostics (theranostics), focused ultrasound (FUS), and molecular imaging (PET/SPECT). The PhD candidate will be responsible for conducting preclinical studies using animal models of glioblastoma, including
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utilizing human cell cultures (2D and organoids), advanced fluorescent imaging, live imaging, FACS, RNAseq + bioinformatic analysis, Click-IT technology, RT-qPCR, Western Blot, and possibly animal experiments
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multimodal brain imaging techniques with novel neuromodulation. More specifically, we work to understand the mechanisms of (mal)adaptive plasticity and develop new treatment approaches for different
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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measuring stand for the collection of hyperspectral data on a test field Collection of imaging data and creation of a database Establishment of a data processing routine for pre-processing the hyperspectral