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Field
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technologies (e.g. transdermal alcohol sensors) and/or virtual reality in research Experience in systematic review methods and/or survey design Familiarity with interdisciplinary or multisite research
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priming and susceptibility to infections. The project aims at understanding how endogenous nucleic acids can contribute to the basal activation of innate sensors. Our group previously studied the role
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conditions, identification of vulnerabilities, and development of resilience enhancement strategies. Contribute to the design, development, and implementation of new models, methods, and algorithms
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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, United States of America [map ] Subject Areas: Physics / Atomic, Molecular, and Optical Physics , Experimental Ultrafast Physics , Metrology , Optics and Photonics , Quantum Optics , Quantum Sensors , Ultrafast Science
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priming and susceptibility to infections. The project aims at understanding how endogenous nucleic acids can contribute to the basal activation of innate sensors. Our group previously studied the role
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programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
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specialist knowledge and experience in data acquisition, signal processing, and data analysis from wearable or non-wearable sensors and devices. You must be able and willing to travel away from Oxford, often
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highly motivated and collaborative Postdoctoral Fellow with an interest in optics, device physics, and/or environmental sensor integration for ocean observation. We are an interdisciplinary group
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optimization algorithms for both estimation and inference. Special emphasis is placed on advancing statistical approaches to address the demands of increasingly complex, high-dimensional, and unconventional data