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Field
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the design, development, deployment and evaluation of NeoShield’s applied machine-learning systems, the machine-learning-driven Clinical Decision Support Algorithm for neonatal sepsis and the real-time ward
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, pharmacovigilance, pharmacoepidemiology methods development). In general you will have opportunities to learn: Understanding of pharmacovigilance workflows; GenAI based algorithm and agent development for causality
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neurodegenerative diseases. 5. Oncomechanobiology: this area focuses on mechanobiological basis of development, stem cells, and cancer, with the aim to discover new pathways of intervention in pathological conditions
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characterization of integrated memristor devices and systems. • Develop algorithms and system-level integration strategies to harness the capabilities of AI accelerator for machine learning and deep learning
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Systems (Mixed-Signal IC Design) Ideal candidates have Specialist Knowledge in Neuromorphic Engineering, with experience in designing and testing Mixed Mode IC systems, working with and/or developing
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, manufacturability, and operational performance in pipeline environments. B. Defect Detection & Multimodal ML Oversee the development of vision-/LiDAR-based defect detection algorithms for cracks, chokage, deformation
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or otherwise) • Lead in translating the developed code into shareable (user-friendly) code for use by students in the Lehman or de Boer groups in the first instance, and then by a wider scientific community via
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of Artificial Intelligence (AI), and therefore a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and
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for, and mitigating weather and hydrological extremes, as well as to develop effective decarbonization strategies. The possible role of AI ranges from predictive models of solar insolation and wind variables
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tools and their integration into the matRad treatment planning system; 3) development of tools that automatically identify for each patient the dose-response models that characterize the worst-case