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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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the PRELIFE program we offer 15 exciting research projects which can be found at http://www.prelife.originscenter.nl of which the research project of the current PhD position is one. This project aims
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PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
the PRELIFE program we offer 15 exciting research projects which can be found at www.prelife.originscenter.nl of which the research project of the current PhD position is one. This project aims at uncovering
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16.08.2023, Wissenschaftliches Personal The Chair of Computational Modeling and Simulation (CMS) at the Technical University of Munich invites applications for the position of a Research Assistant
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FLOW research group is a young, dynamic group working in the fields of thermodynamics, fluid mechanics, and data-driven modelling. At the Department of engineering Technology (INDI) — Thermo and Fluid
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programming, modelling, and data analysis skills. Experience with formulating and solving mathematical optimization problems is an asset. Proficiency in English is required; good comprehension and oral skills
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31st August 2025 Languages English English English Vacant Post doc position 2 years PostDoc in ocean biochemical modelling Apply for this job See advertisement About NORCE NORCE is a forward-looking
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
function of these cell envelopes for several bacterial species. The most powerful models have several parameters set from experimental observations, in this case data gathered through the use of electron
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using experimental data from laboratory setups Validate models through targeted measurements and structured testing procedures Analyse loss mechanisms and system efficiencies under various operating
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. The goal is to build foundation models capable of learning from richly structured or semi-structured data where traditional graph neural networks may fall short, enabling better representation, inference