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Field
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knowledge from your former experience on relevant topics, including Trustworthiness in AI and its verification, AI Risk Management Frameworks, AI policy, regulation, and governance mechanisms. Fluent
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numerical approach The PhD is part of a Franco-German co-funded project between IFP Energies Nouvelles (IFPEN) at Lyon and the Hamburg University of Technology (TUHH), focusing on the modelling of gas/liquid
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research in Artificial Intelligence and its ethical, frugal, and sustainable dimensions? Do you have a PhD and a solid experience in research or R&D in AI, with a specific interest in designing models
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modelling of cognitive processes. Fluent in statistical code in either R, Python, or Matlab. The advantage is Previous work on social cognition, decision-making, moral psychology and related topics
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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) matrix architecture are influenced by the mechanical and geometric properties of their environment. These computational models can provide crucial mechanistic insights into the key parameters governing
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Na+ transport, interfacial phenomena, and performance degradation induced by e.g. salt accumulation or Al deposition. By leveraging your experimental data with the modelling approach
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. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method combining machine learning and biophysical modelling to model embryo
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for integrating geothermal plants into European energy system models based on the institute`s own open-source FINE framework github.com/FZJ-IEK3-VSA/FINE . Your tasks in detail: Implementing geothermal
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department in the ISSA expertise center that develops advanced AI solutions involving AI models, algorithms, implementations, sensors and hardware for small scale edge up to large scale distributed and hybrid