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. Expertise in artificial intelligence and machine learning. Recent research experience in the development of first-principle wave models. Recent research experience in the development of numerical codes
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, binary black holes, binary neutron stars, and black hole-neutron star binaries). The broader goals are to generate accurate predictions for gravitational-wave and multimessenger signals and to explore
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: January 19, 2026 (for full consideration) Apply online at AJO: https://academicjobsonline.org/ajo/jobs/31255 The Center for Data Science for Enterprise & Society at Cornell University seeks to recruit
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
the use of renewable ocean energy at national and global level and address the issue of climate change and carbon emissions, with particular emphasis on wave energy or its hybridisation with offshore wind
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team members to ensure all project deliverables are met. Undertake these responsibilities in the project: Resistance Analysis: Conduct simulations to analyze wave interactions, buoyancy, and stability
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background in wave optics, Fourier optics, and inverse problems, including experience with linear and nonlinear reconstruction methods (e.g., Born/Rytov approximations, multislice or multiple-scattering models
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microscopy, optical diffraction tomography, or related computational imaging methods. Strong background in wave optics, Fourier optics, and inverse problems, including experience with linear and nonlinear
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, Dark Matter , Exoplanet Imaging , Exoplanets , Experimental Astrophysics , Extragalactic Astrophysics , Galaxy Formation , Gravitational Waves , High Energy Astrophysics , Instrumentation/Observation
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the SW Portuguese coast; Analysis of wave and tidal data for the Portuguese SW coast (Sines buoy/gauge and global models); Evaluation of rip current occurrences and their association with embayment and
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in