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Field
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physical techniques. Responsibilities and tasks: • In-depth and extensive bibliographic study; • Optimization of the crystal growth process through numerical models; • DFT and DFT+eDMFT studies
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Research or a related field Strong knowledge of quantitative and/or computational research methods, ideally in numerical optimization and simulation models. Proficiency in one of the major programming
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to design optimized growth media for animal cells lines used in biotechnology. This work involves the development and application of genome-scale metabolic models to characterize cellular growth and
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The candidate will develop numerical procedures in
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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoctoral Researcher on hybrid AI-optimization modelling The Energy Science Center (ESC) at
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but not limited to: o Quantum error correction, fault tolerance, and resource optimization. o Entanglement dynamics, quantum control protocols, and hybrid quantum-classical algorithms. o Modeling and
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and economy that respect people and their environment. We are looking for our future postdoctoral researcher in optimization for statistical learning to join the Image, Data, Signal (IDS) department
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numerical methods for the inverse design of nanophotonic structures enabling broadband, multiparameter sensing in fiber-based systems. The project is a collaboration between AMOLF, TU Eindhoven, and
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quantification of pigments and binders. The work will include the generation of simulated spectral data based on physical models, the training and optimization of machine learning models, and their validation
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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor