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relevant to the project, such as physics. Fluency in English, both in oral and written forms, is mandatory. The candidate should have a strong interest in physics (especially optics), numerical methods, and
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deep learning frameworks (e.g., PyTorch, TensorFlow, and JAX). • Experience in PDE/ODE modeling and numerical methods. • Strong interest in interpretable ML and mechanistic model discovery. Submit a
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) and theoretical perspective, in collaboration with the “Numerical Astrophysics” research team. Research topics at the IAC include most areas of astrophysics: Solar Physics (FS), Exoplanetary System and
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potential lends itself to this. Required profile: · With a PhD in physics or mechanical engineering, the successful candidate will have acquired solid skills in the mathematical and numerical methods
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tasks that best suit your strengths. This could involve the design, optimization, and fabrication of advanced devices using numerical methods like FDTD; taking charge of spectroscopic experiments
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; factors contributing to differential heat/pollution effects across population with varying characteristics vulnerabilities; and use of causal inference methods to estimate health effects of hypothetical
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of disease-related biomarkers, and study of organ-on-a-chip. We develop microfluid, optical and electrochemical methods in combination with microorganisms and cells to provide solutions for environmental and
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focuses on innovation, entrepreneurship and collaboration with business and industry, and numerous researchers from the department have established companies to develop new medicinal treatments founded in
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Job Description Would you like to join a team that supports the green energy transition by developing wind turbine response and validation methods and solutions? We are seeking a highly motivated
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology