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(CI) to design, build, and optimize high impact computational tools, algorithms, and analytical workflows that power innovative research in medicine. You’ll manage and analyze large datasets and
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performing ongoing reassessment to ensure optimal outcomes. This role delivers both individual and group education to patients, families, and caregivers, supporting understanding of nutrition-related needs and
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digital de señal y lógica de control en tiempo real. - Optimización de uso de recursos, consumo energético y rendimiento temporal (timing closure. Implementation and optimization of hardware logic using
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Machine Learning-driven Autonomous Systems for Materials Discovery and Optimization NIST only participates in the February and August reviews. We are developing machine learning-driven autonomous
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NIST only participates in the February and August reviews. We are developing machine learning algorithms to accelerate the discovery and optimization of advanced materials. These new algorithms form
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algorithms and system frameworks that optimize cost, performance, and scalability. The role focuses on leveraging machine learning and reinforcement learning to enhance storage and service efficiency under
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Orthopaedic clinic leadership in the identification, development, and implementation of strategies designed to optimize patient access. This role is responsible for access analytics, provider template
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platforms. You will play a key role in administering, programming, and optimizing systems such as the Schools Learning Management System (i.e. Canvas), the Student Information Systems (i.e. Campus Solutions
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electric mobility and smart energy management. We design and implement charging infrastructures and advanced energy optimization systems, combining engineering, proprietary software, and strategic vision
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 7 days ago
position within a Research Infrastructure? No Offer Description Job Summary/offer: To optimally use the resources in veterinary care, it is important to capture, preprocess, and model the existing data