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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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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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manufacturing framework using the IEEE 1451. Work Plan: Develop a digital twin concept capable of fulfilling the requirements for PPS14—Predictive quality control system for welding, WP9: control systems
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supervise students (BSc/MSc/PhD) in competitive research environments. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-pdi-postdo… Requirements Research
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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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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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patient-specific, predictive models using real-world clinical data. The project aims to enhance understanding of disease trajectories, optimize treatment strategies, and support real-time clinical decision
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The Human Motor Control and Neuromodulation Lab under Dr. Helen Bronte-Stewart is part of the Stanford Movement Disorders Center within the Department of Neurology and Neurological Sciences
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, and control of infectious diseases. They will collaborate with other researchers, public health agencies, and stakeholders to provide insights and guidance for disease prevention and intervention
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-based textile fibres. Experience in the design and validation of particulate systems for the controlled release of bioactive molecules to promote skin tissue healing and regeneration. Experience in