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scientists, clinicians, and engineers to push the boundaries of brain imaging and contribute to insights that can improve healthcare practice. Technical PhD Candidate In this role, you will be responsible
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quality that is not visible in blood or clinical characteristics. By combining the results of AI-driven image analysis of histological samples conducted in this PhD project with biomarker data and outcome
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simultaneous stimulation of these processes increases aggregate clearance. This project will employ a combination of advanced cell biology, molecular biology, live-cell imaging, and proteomics approaches. Your
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team of experienced researchers in imaging, machine learning, oncology, and pathology. We do not discriminate on the basis of sex, gender, belief, culture, place of birth or occupational impairment when
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and Thesis Finalization: Synthesize findings and document the research process, results, and conclusions. This will culminate in the finalization of the PhD thesis, presenting a comprehensive
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chip prototype, improving performance and durability in automotive applications. Specifically, this PhD project focuses on memristive materials as electronic realizations of the hysteron concept
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of brain imaging and contribute to insights that can improve healthcare practice. Technical PhD Candidate In this role, you will be responsible for developing and refining MRI technologies to visualize brain
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language models, deep learning, and information retrieval? The Information Retrieval Lab (IRLab) at the University of Amsterdam is looking for PhD candidates to join our research team and contribute
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PhD candidates to work on topics in Generative Information Retrieval (GenIR), a new and rapidly evolving retrieval paradigm where generative models are used to directly generate document identifiers
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on the development, optimization, and clinical evaluation of new x-ray-based imaging methods. The lab focuses on the use of medical physics approaches to improve image acquisition methods and processing algorithms