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latest issues that impact our society and are offering you the chance to actively help in shaping the change! We offer ideal conditions for you to complete your doctoral degree: Supervision and support by
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unique atmosphere where there is expertise to dig deep into computational modelling, while remaining connected to the experimental side. This interdisciplinary atmosphere has been a main catalyst for many
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data, the consortium aims to develop a robust model that can better predict transplantation outcomes. This innovative approach will contribute to more reliable donor kidney selection, reduced rejection
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unique atmosphere where there is expertise to dig deep into computational modelling, while remaining connected to the experimental side. This interdisciplinary atmosphere has been a main catalyst for many
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that the developed methods are robust, adaptable, and grounded in real-world practice. You will apply advanced techniques such as agent-based modelling, quantitative resilience assessment, and risk analysis to
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conditions. Profile: Required degree: Master's (M2) in Ecology and Evolution - Specialization: Modeling in ecology and evolution, theoretical ecology Expected skills: - Statistical analysis - Mathematical and
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. The work includes both theoretical modeling and experimental validation, addressing development of software-defined power electronics, droop control adaptation to weather conditions, integration with
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complementary expertise, using both space and ground-based observations of the solar atmosphere, in-situ measurements from heliospheric probes, in synergy with a complete numerical modeling of the generation and
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of core web technologies. You have solid experience in Python and JavaScript programming languages. You preferably have experience with building and using machine learning models. You care deeply about
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transfer learning to transpose the recurrent neural network (RNN) model available for supercritical CO2 power cycles to other cycles. Since thermodynamic conditions vary greatly depending on the fluid and