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Field
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Join a dynamic team of motivated individuals with deep collective experience throughout digital forensics, incident response, investigation, operations, and academic research. We seek individuals
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Join a dynamic team of motivated individuals with deep collective experience throughout digital forensics, incident response, investigation, operations, and academic research. We seek individuals
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scientific initiative focused on AI-assisted reverse engineering of integrated circuits for hardware assurance and intelligence analysis. The project is conducted within the Deep Learning for Perception and
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-content microscopy and AI/deep-learning-supported image analysis will be used to quantitatively assess neuronal morphology and maturation. Parameters will include dendrite length and branching, axon growth
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to the development of sustainable materials for the hydrogen economy. You are an independent thinker, eager to learn new experimental techniques, and enjoy collaborating with researchers from different disciplines as
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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computational methods with a particular focus on deep learning and image analysis. The project relies on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP
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. There is also a need for accounting noise in Deep Learning models and quantifying uncertainty in real-world applications. This PhD studentship (scholarship) leverages large-scale Earth Observation data
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data science, biomedical engineering, technical medicine, or a related field. You should have strong programming skills (Python, PyTorch), deep learning knowledge (multimodal learning, longitudinal
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/Qualifications Skills in acoustics and audio. Prefereably skills in machine learning and deep learning. Specific Requirements Education in acoustics. Knowledge of acoustical measurement techniques, as