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Field
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available for enthusiastic candidates interested in furthering their interests/knowledge in the control of agricultural insect pests. The overall research goal of the group is to develop new pest management
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, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno-economic study, design and analysis of integrated systems. Experience with energy system
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. Scale and optimize fabrication and cryogenic testing workflows. Characterize detector and system performance, including detection efficiency, dark count rate, timing jitter, and yield. Develop packaging
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include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and full-scale structural testing of sleepers under static and
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and validate railway sleepers made with UHPC. The work may include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and
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, plant water/nutrient hydraulics, chlorophyll fluorescence, and root system architecture adaptation. Controlled (greenhouse/glass house/growth chambers) and field research experience. Comprehensive
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(EMT) simulations. Evaluation of grid control strategies for increasing PV hosting capacity, including active/reactive power control, voltage management, reactive power compensation (SVC/STATCOM), energy
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. The successful candidate will lead efforts to develop novel electrical readout, control, and sensing architectures that complement or potentially replace conventional optical detection methods. The research will
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Organization Centers for Disease Control and Prevention (CDC) Reference Code CDC-2026-0095 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A
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on integrating an agentic platform for electrocatalyst discovery and developing novel machine-learning algorithms (e.g., reinforcement learning) for materials discovery and process optimization. The candidate will