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changes either at the hardware or software levels, such that the target system reaches unexpected states or follows unexpected execution paths. Reaching such unexpected states is then leveraged in attacks
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defined with the successful candidate). Salary level will depend on the experience of the candidate recruited (post-docs who have just completed their thesis are very welcome). It will take place at CEA
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experiments. The objective is to develop Bayesian causal models and neural networks capable of identifying relevant causal relationships between instrumental parameters and observed anomalies. The work will
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international partners, building a robust network for your career. · Life in Paris & Beyond: Work on a vibrant campus just 20 km from the heart of Paris, enjoying the city’s cultural and scientific
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to the lithographic process such as overlay; - Interact and work with a PhD student focusing on the data modeling to understand the acquired data and explore the limitation of the Low Energy SAXS technique; - Define
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., cores, memory hierarchy, accelerators, interconnects) and software-level decisions (e.g., task mapping, scheduling, compiler optimizations), which together lead to a combinatorial explosion of possible
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outsourcers. Data analysis basics (with Python or MatLab) is also demanded. General knowledge about embedded software programming may be required (but not compulsory).
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Organize training sessions Library packaging and deployment The successful candidate will master the following skills and knowledge: Proficiency in modern C++ (C++14 and above) Software engineering and