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project focused on sustainable polymer synthesis from CO₂. The researcher will develop and apply computational and AI-based methods, including high-throughput quantum chemistry and machine learning
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artificial intelligence (AI) methods that propose, prioritize, and interpret experiments, accelerating the discovery and optimization of catalytic materials for energy and sustainability applications
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factor > 0), that spontaneous and precipitated withdrawal have DISTINCT temporal architectures, and self-excitation indexes withdrawal severity (including anxiety-like, negative-affect-proxy behaviors
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of understanding mechanism and therapeutic platform. We hypothesize that both spontaneous and precipitated opioid withdrawal are self-exciting (branching factor > 0), that spontaneous and precipitated withdrawal
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to contribute to its portfolio of research. The Postdoctoral Research Associate will develop new computational methods in knowledge-grounded artificial intelligence, systems modeling, natural
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methods. • Strong publication record in leading engineering or scientific journals. • Experience with MEMS fabrication processes and device characterization. PREFERRED QUALIFICATIONS: • Experience
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researcher to start in February 2026. The primary responsibility of the postdoc is to perform basic or applied research of a limited scope, primarily using existing theories and methods, ensuring
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. Work will emphasize the development and analysis of advanced methods in areas such as sparse signal recovery, compressed sensing, and statistical estimation, with a particular focus on their role in
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using various methods, technologies for printed electronics, tactile sensing and haptics, electronic skin and its application in robotics and wearable systems. Knowledge of simulation tools (e.g
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. The research focus is on developing and applying first-principles-based and data-driven computational methods to understand multiscale processes and accelerate chemical discoveries for renewable energy