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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
beneficial properties; their industrial applications include hard alloys and ceramic-metal composites for cutting and wear-resistant tools, protective coatings, and furnace and aerospace turbines. Together, we
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; their industrial applications include hard alloys and ceramic-metal composites for cutting and wear-resistant tools, protective coatings, and furnace and aerospace turbines. Together, we will identify and push the
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to explore the mechanical, electrical, and/or thermal properties of the fabricated materials, such as tensile stress and nano-indentation. The project will for example characterize the coefficient of thermal
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in electric fleet planning and management, and in integrated transport and energy management systems. This will likely result in publication of at least three high impact factor journal papers in
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attack/defense mechanisms. Hands-on experience with Android malware detection and reverse engineering Experience with explainable AI (XAI) techniques (LIME, SHAP, attention mechanisms, etc.) Proven
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unique training environment to advance microbiome science through metaproteomics. The program addresses One Health challenges by integrating research on microbial mechanisms, microbiome dynamics in various
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vulnerability detection. Explainable detection pipeline: you will investigate and document the mechanisms through which LLMs identify software vulnerabilities, creating an interpretable detection framework
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engineering, microscopy, and chemical biology to investigate neuroimmune interactions and mechanisms underlying neurodegeneration, both through in vitro studies and in the context of neurological diseases. We
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, as well as mechanical, electrical, and/or thermal property measurements. The candidate will work at LIST (Belvaux) and have regular contact with the company, with some experimentation possible
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autoencoders, robust PCA, wavelet transforms). · Experience in methods to disentangle and integrate data sources (e.g., InfoGAN, β-TCVAE, TopDis / Topological Disentanglement, Independent Component