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Field
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algorithm-based technologies in service occupations, with a focus on how collective bargaining and other forms of collective worker voice influence these strategies and worker outcomes. The US research will
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force‑responsive probes, DNA‑based sensors, or advanced microscopy to understand mechanochemical signaling in cells. Operate and innovate with state‑of‑the‑art optical, fluorescence, and force
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will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted
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to, benefit-harm analysis of cancer early detection tests, development of clinical decision rules in cancer early detection leveraging Electronic Medical Records (EMRs), and development of EMR-based algorithms
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We are seeking motivated researchers with expertise in large-area 2D materials growth for sensor and transistor applications. The focus is on developing wafer-scale 2D materials using CVD, PLD
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sensor data, public databases, and GIS. Predictive Modeling:Design predictive models to evaluate the impact of urban and environmental policies on public health. Interdisciplinary Collaboration:Collaborate
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with IoT technologies (smart sensors, connected devices) for real-time monitoring of waste systems. Circular Economy: Familiarity with circular economy principles as applied to waste management
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data, metabolomics and/or proteomics. Develops robust pipelines for data annotation, analysis, and quality control. Creates analytical algorithms and tools to address scientific questions with big data
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needs. Tasks may involve CAD design, machining, and integration of sensors and control systems. Collaboration and Mentorship 5% Work collaboratively with faculty, graduate students, and other postdoctoral
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EEG HydroCel Sensor system and Net Station software and interest in the microstructure of infant sleep would be a plus. The successful candidate is expected to lead their own project, support other