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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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questions related to the molecular regulation of autophagosome formation, using cell biological, genetic, and imaging-based approaches. The candidate will explore the function and regulation of proteins
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cancer cell imaging including digital holographic live imaging of cancer cells to assess cell motility. Experience with mass spectrometry of protein modifications is demanded (including sample preparation
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preparation for imaging Strong programming experience with C/C++ and the ROOT data analysis framework is required Desired qualifications (can be waived): Understanding of data processing pipelines in nuclear
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of the following areas will be a merit. Advanced AI methods development in Python or any other relevant programming language Computer Vision and image analysis Handling of large dataset Qualifications Applicants
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for clinical AI based on patient data from heterogeneous sources notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI
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interdisciplinary team will develop a machine learning based monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate relapse
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affect of sleep on brain health and cognitive processes. Magnetic Resonance Imaging (MRI) is used in the project in combination with cognitive, neuropsychological and somatic assessments. The position will
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for Cognitive and Clinical Neuroscience (CCN) combines research in human cognition with the application and development of advanced methods in neuroscience and neuropsychology. Methods for brain-imaging and brain
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written and oral English. Experience from one or several of the following areas is an advantage: Programming, image processing and machine learning. Magnetic Resonance Imaging. Laboratory experience from