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Field
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PhD in Biological Sciences or a related discipline Preferably, prior professional experience as a Postdoctoral Researcher Proficiency in cell culture techniques, ideally including 3D cell culture models
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. The work involves analysis of numerical dynamo simulations using quantitative metrics derived from the most recent global paleomagnetic reconstructions, and applying data assimilation to recover extreme core
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. The project activities will involve the development of the theory and implementation of the advanced mechanics and numerical models as well as constitutive model calibration and validation based on physical
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. The successful candidate will contribute to studies of time-averaged geomagnetic field morphologies and core dynamics during transitional events. The work involves analysis of numerical dynamo simulations using
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for the TARGET-SEQ project Conduct bioinformatics analysis and implement new tools Collect, interpret, and analyse research related data and results Ensure proper scientific documentation Document performed
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supervise cutting-edge interdisciplinary research building on the analysis of large-scale blockchain data. This will include, but is not limited to: Designing, implementing, and maintaining scalable pipelines
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or hybrid solar systems. Experience with numerical modeling (e.g. MATLAB/Simulink, Modelica, COMSOL, or similar) and data analysis. Familiarity with heat pump systems, building energy simulations, or control
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financial crime prevention, performing the following tasks: Conduct and supervise cutting-edge interdisciplinary research building on the analysis of large-scale blockchain data. This will include, but is not
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Requested start date: 01/10/2025 Contract type: Post Doctoral Education: Doctoral (PhD) Experience : 1-5 years You hold a doctoral degree (obtained less than 3 years ago) with a specialization in numerical
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understanding of non-stationary complex systems through theoretical analysis and numerical simulation develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time