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young lab, you will benefit from opportunities of high research independence, extensive discussions, and rapid iteration of tested ideas. If you are passionate about uncovering the fundamental principles
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applications. Candidate(s) of the contest holding qualifications obtained abroad must prove the recognition, equivalence, or registration of the doctorate degree, under the applicable legislation. This formality
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 2 months ago
, and testing of detector components using the UNH test stand. Analyze test beam and cosmic ray data to characterize detector response. Collaborate with hardware engineers and software developers
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solution(s) (hardware + software) could address such limitations? Please structure your research proposal highlighting how you plan to capitalise on your previous work and experience. . In particular, you
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machine learning. Essential Duties and Responsibilities: Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software
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from advanced centrifuge tests with numerical simulations. We are looking for candidates with a PhD in geotechnical engineering and proven experience in numerical modeling of offshore foundation systems
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future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion
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research on new models integrating terrestrial plant biodiversity, ecosystem productivity, hyperspectral remote sensing and airborne LiDAR to test prominent hypothesis of the effect of tree diversity
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: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine learning and artificial intelligence models focused
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predictive modeling and allowing for scenario testing in precision medicine; Applying transformer-based architectures to model sequences of clinical events and other time-ordered data to predict the future