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problems in bioinformatics. This project is part of the Faculty of Science's new Quantum Simulation for Molecular and Material Design (Q-MMD) programme. You will join a growing interdisciplinary team at
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challenging, especially in dunes with complex topography. Your job In this 2-year postdoc position, you will use numerical modelling and machine learning techniques to increase the accuracy of coastal dune
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fluxes and acidification in global marine P cycling through a combination of field work in the North Atlantic Ocean, laboratory experiments and numerical modelling. A scientific cruise with our research
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themselves. In this project, you will investigate whether and how large offshore wind farms influence precipitation. Using high-resolution numerical modeling, you will examine the physical mechanisms through
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Python. Close scientific collaboration with researchers in fluid mechanics, theory, and numerical simulation at ARCNL, TU/e, and UvA. Possibility to enhance your experimental research work with advanced
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. Depending on the candidate's background and interests, the project may also involve acoustic hardware, numerical simulations, phantom development, and translation of the resulting methods toward biomedical
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which factors determine feasibility and performance. What will you do? Improve, document and apply a regional groundwater model for variable-density flow groundwaterflow and coupled salinity simulations
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physics/mechanics. Experience with and enthusiasm for numerical simulation tools including programming in fortran/python. A research-oriented mindset: critical thinking is your second nature. A team player
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific
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science or remote sensing, or a related field. Good programming skills (e.g., Python). Familiarity with satellite data or other large numeric data files. Knowledge of physics or biophysics. Knowledge