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Field
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advance the ability to predict disease progression and response to specific therapies. The details of the research direction within the project frame will be decided in a dialogue between the postdoctoral
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is important to control their operating temperature and improve the dissipation of the heat generated during operation. The study is divided into 3 tasks : • task 1: the first task is devoted to a
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of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders
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imaging program involving molecular oncologists, cancer biologists, computational biologists, and imaging scientists focused on detecting breast cancer and predicting response to therapy. The position is
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) multi-omics analysis for the identification of therapeutic targets (biomarkers or druggable targets). The candidate will also develop and implement AI-driven tools to predict disease prognosis and
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vibratory extraction and jetting, supported by experiments at multiple scales and advanced numerical modelling. By studying ageing effects on extractability and predicting mechanical responses, the project
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Institute, you will play a vital role in advancing bioinformatics tools and pipelines to help prevent and control foodborne diseases. Food- and waterborne diseases continue to pose major public health
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analytics that support precision care in mental health. We have a strong interest in determining the clinical, neural and genomic features that predict the course of childhood mental challenges as
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corrosion and embrittlement in reactor environments, remains incomplete, and key mechanical properties are scarce. Without reliable experimental data, our ability to develop predictive models
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determining the clinical, neural and genomic features that predict the course of childhood mental challenges as well as response to treatments. The role also provides the opportunity to gain experience in data