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environmental thresholds for mangrove establishment and coastal protection. This computer modelling step may be elaborated by the PhD student or another post-doctoral researcher working on the project, depending
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future material development to more effectively treat arthritic diseases. As a project assistant with us, you will work with cell culture as well as model design and development in the context of arthritis
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dioxide removal (mCDR) and aquaculture. The ideal candidate will have experience in two or three of the focal areas: data driven modeling, scientific machine learning or coastal ocean physics; and will have
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Sustainable Development Goals (SDGs). Critics, however, contend that the blue economy leads to new territorial and resource conflicts, displacements of coastal communities, and degradation of ecosystems because
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of the Systems and Control division focusing on data-driven control methodologies. About the research project Model-based control is arguably the prime framework to perform certifiably-safe regulation
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. Experience with Python programming and QuTip simulation. Experience of working on quantum computing or quantum information. Familiarity with modeling quantum properties of superconducting circuits, both
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: Experience: in numerical modelling applied to the study of sediment dynamics and coastal morphodynamics; in the production/publication of scientific papers and technical reports; in the development of projects
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link
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additional tasks include to improve our main simulation tool (Atmospheric Radiative Transfer Simulator, https://www.radiativetransfer.org/ ), to apply the derived geophysical data for verifying climate models
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Internal Number: 6779182 Assistant Professor - Geospatial AI & Coastal Hazards College: College of Science and Engineering - 323 College Dept/School: Earth and Ocean Sciences - 32341 Vacancy Number: 16F-716