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Field
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(especially silicon-based) and cathode applications. In this role, you will: Develop new binder systems for electrode processing. Synthesize and modify binders for innovative manufacturing processes. Balance
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an integrated development of network architectures, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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within LTU’s AIC³ Lab (Automation, Industrial Computing, Communication, and Control Laboratory). Subject description The research subject focuses on an integrated development of network architectures
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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. The research team focuses on developing novel methods to extract knowledge from data, modeling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but
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funded by a EU programme Reference Number 304--1-14162 Is the Job related to staff position within a Research Infrastructure? No Offer Description Join a research team developing state-of-the-art open
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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experience in experimental particle physics and data analysis Prior experience with machine learning tools Prior experience in developing algorithms such as particle identification, specific final state event
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can reduce model accuracy, especially when modeling multiple processes that interact across different spatial scales. To address this, the project will develop a new class of raster data-processing