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                Field
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                approaches to avoid costly design and fabrication cycles for the optimization of these circuits are possible, in particular the use of Look-Up-Table (LUT)-based techniques that exploit the characterization 
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                the analysis of voting rules using robust and interpretable mathematical tools. It explores the writing of voting modes as the result of an optimization problem. Based on statistical depth functions 
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                The PhD work will take place in the framework of the ANR funded HENBoS project (2025 – 2029), which seeks to describe with unprecedented accuracy and scope massive black hole systems as cosmic accelerators 
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                influence helps detect labeling errors or prioritize unlabeled images, optimizing the learning algorithm and service quality. The doctoral student will carry out their work at IMAG (UMR of Mathematics) and 
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                active material at the voxel level– except for certain composite hydrogels and materials with a high coefficient of thermal expansion – which demands specific deposition orientation for optimal performance 
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                , extinctions, and environmental change; ● Running simulations and scenario analyses to explore how different discounting rules or time preferences shift optimal conservation choices; ● Fitting models 
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                this context, deep eutectic solvents (DES) appear to be a more sustainable alternative: low volatility, increased stability, high flash points, and promising performance. However, their use is still emerging and 
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                of the generator and the expander (with cold and hot air using a “linear mechanical” brake), to determine the intrinsic performance of each component and validate the models for optimal control via generator 
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                department at IETR in inkjet-printed OTFT fabrication and is part of the ANR-funded SMOOTH (Stable Metal-free Organic transistOrs Thanks to Homojunction) project, which will start in February 2025 and run 
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                rich and diverse process database. The idea is to identify as many potential solutions as possible, which will feed into a superstructure optimization (in another work package) that will then identify