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thin films and photovoltaic devices; execute a staged fabrication pipeline spanning candidate selection, thin-film deposition, high-throughput device fabrication, and high-performance device fabrication
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perform quantitative image analysis. Perform molecular and cellular assays (flow cytometry, immunofluorescence, qPCR, etc.) to characterize immune and tumor phenotypes. Collaborate with biophysicists, cell
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Programming Systems R&D: Contribute to DOE goals of enabling performance‑portable high‑productivity languages (Python/Julia/Rust) and evaluate the emerging role these languages and frameworks within scientific
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perform experiments related to identification of somatic variants leading to inborn errors of immunity, with oversight from PI. Write manuscripts describing the findings of your scientific research
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magnetotransport). They will analyze device performance metrics such as output signal, switching speed, energy consumption, endurance, and scalability, and benchmark them against existing technologies (CMOS, MESO
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, including language, gestures and eye-tracking data. Perform joint analyses of multimodal data. Write up the output papers, including the relevant literature review (covering linguistic typology and language
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microscope iii) high-performance computing resources iv) access to state-of-the-art facilities (ESRF, HPC Jean-Zay) The team is young, dynamic, and strongly focused on integrated approaches in structural
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Associates. Job Duties Conducts in vitro cancer biology experiments, including 2D culture, 3D organoids, spheroids, and patient-derived models. Performs CRISPR/Cas9-mediated gene knockout (KO), siRNA/shRNA
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that houses advanced 3T human and 9.4T preclinical MRI scanners, both equipped with ultra-high-performance gradient systems. MINIMUM REQUIREMENTS Education: Applicants must hold a doctoral degree, preferably a
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
, and real-time classroom monitoring. Design and implement machine learning models to analyze multimodal data (e.g., student behavior, engagement, and performance) to enhance personalized learning