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significant optical losses at interfaces between materials or components. These constraints hinder the deployment of compact, high‑performance, and industrially competitive photonic systems. In this context
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research assistants, and learn to design, perform, and analyze experiments. This position will work with animals (mice), specifically working on mouse colony breeding and performing PCR genotyping analysis
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blood samples to advance patient care. This role will involve developing computational models (statistical, machine learning, etc.), and using them to perform high throughput analysis of clinical data
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–property–processing relationships relevant to high-field and high-temperature dielectric performance to inform the digital discovery of new polymers. Characterize materials, interfaces, and film morphology
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will work with Prof. Daniel Eisenstein and collaborators on the analysis and interpretation of JWST data, with particular emphasis on deep-field observations. The position provides access to large, high
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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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datasets. Experience with GPU-based training and high-performance computing. Interest in translating methodological contributions into high-impact medical AI venues (e.g., Nature Medicine, Nature Machine
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materials. Create a new flame-retardant electrolyte for sodium-ion (Na-ion) batteries. The ultimate objective is to produce a high-performance hard carbon-based sodium-ion battery system, contributing
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the Faraday Institution, investigating degradation mechanisms in next generation Li-ion batteries. You will perform research into degradation reactions occurring at electrode-electrolyte interfaces in next
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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