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false positives and maximizing robustness. Validate the pipeline using diverse and regulatory-relevant samples, supporting future accreditation. You will work closely with a multidiscip... For more
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working on a third-party funded project funded by the Luxembourg National Research Fund (FNR) on 'Rule of Law Principles - which model for the Global South?' The project focusses on the transition
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Applications are invited for a 1-year post-doc position on modeling of two-phase flows for green hydrogen application at the Department of Mechanical and Production Engineering, Aarhus University
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a job opportunity for an experienced post-doctoral researcher specializing in computational modelling of materials and structures, with a focus on impact modelling of composites. In the framework of a
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, stimulation and transduction of T cells, and standard molecular biology methods, including cloning. Experience with flow cytometry and animal work is essential. Hands-on experience using cancer models in mice
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transfer our knowledge to society. We are doing this according to our vision: “Taking the pulse of our Earth to safeguard a habitable planet”. For section 2.5 Geodynamic Modelling (department "Geophysics
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for the local energy community. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be mainly in charge of: · Generating models and simulating
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modelling starting as soon as possible. Job Description The main tasks will include modifying mesoscale eddy parameterizations in an Earth system model, implementing centennial climate change simulations with
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using the EC-Earth earth system model, running simulations to test the robustness of Arctic-lower-latitude interactions in collaboration with colleagues at the Danish Meteorological Institute. Investigate
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Postdoc position (f_m_x) ,,Combining Physics-Based Machine Learning and Global Sensitivity Analys...
order reduction approaches using machine learning models for the simulation of thermo-hydro-mechanical (THM) processes Generation of predictive maps to evaluate the potential of induced seismicity Further