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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter
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of the numerical methods behind CFD and turbulence models. Experience in analyzing CFD data and interpreting simulation results. Excellent command of written and spoken English. Experience writing scientific reports
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
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. However, current estimates of methane emissions from inland waters to the atmosphere are highly uncertain because of limitations in long-term observational data and modelling methodology. In this four-year
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conditions. Environmental effects on electronics are an important area today due to the widespread use of electronics such as electrification of vehicles and use in connection with renewable energy systems
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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using mouse models. Contact For further information about the position, please contact Associate professor Luis Hortells: email: Luis.hortells@uit.no phone: +47 77644517 Jon Terje Hellren Hansen via
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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theories and numerical methods, carrying out and analysing field and remote sensing observations and conducting and analysing numerical model simulations. The PhD position is funded by the German Research