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and predictive confidence, including sensitivity and identifiability analyses Compare grey-box models against purely mechanistic and purely data-driven approaches Optimize model performance
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(MSCA-PF) to pursue a career in research. We invite applications from promising young researchers within the field of Computational Biology & Ecological Modeling. The selected candidate will write a
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industrial partners and spin-offs, together with KTT Business Developers and Innovation Managers. Develop standardized, technology-adapted licensing models and agreement templates (exclusive/non-exclusive
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-edge in silico, in vitro, and in vivo technologies to understand, predict and treat thrombosis? This is your chance!! Our goal: Develop multi-level thrombosis risk prediction models by integrating
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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rate and provide a stipend of no less than the standard UK Research Council rate (currently set at £20,780 p.a.) for 4 years. Please note the eligibility criteria set out by the UKRI at: https
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expertise in the use and development of AI-based approaches for image and data analysis. A general understanding of methods for in silico prediction, modeling, or data integration and/or of experimental
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biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run high-performance numerical experiments
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applied in particular to the modeling of 3D-printed concrete at the Navier laboratory, to better predict complex phenomena such as material curing and crack formation. Where to apply E-mail jeremy.bleyer
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Job related to staff position within a Research Infrastructure? No Offer Description Do you want to be trained to develop multi-level thrombosis risk prediction models by integrating insights from