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Field
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Center for Devices and Radiological Health (CDRH) | Silver Spring, Maryland | United States | about 17 hours ago
applied to whole slide images, including understanding performance metrics and validation framework Gain Proficiency in imaging AI pipeline development and optimization Acquire hands-on experience in
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; Develop and apply high-throughput strain engineering and screening workflows to optimize genetic constructs and characterize strain libraries; Mentor research assistants, graduate, and undergraduate
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, e.g. in Python, particularly for machine learning Experience with machine learning theory, evaluation metrics, algorithmic fairness, statistics, or optimization is an advantage Language requirement
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Dynamics (CFD) simulations to optimize the design and performance of floating breakwaters. Develop finite element models for stability assessment, structural integrity, and dynamic response of floating
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storage, demand‑side management, and hybrid PV–wind systems. Development of optimal strategies for increasing grid hosting capacity considering power quality, voltage stability, and losses. The research
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sources and quantum emitters on photonic platforms. Development of on-chip quantum light sources for quantum information applications. Fabrication and optimization of quantum photonic devices and circuits
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methods (e.g., filtering, factor graph optimization, moving horizon estimation) with learning-enhanced components, including meta-learning approaches for adaptive and generalizable estimation. The candidate
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focused on HIV prevention. Key Responsibilities Data Analysis and Interpretation • Contribute to design, execution, and ongoing optimization of the hybrid trial evaluating COAST-AL
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proteins for high quality alternative protein foods including through high moisture extrusion. Key responsibilities will include: Explore innovative methods for food process optimization including the use
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healthcare solutions. Key Responsibilities: Develop and optimize flexible electronic devices, including sensors, actuators, and integrated circuits for health monitoring / wearable robotics applications