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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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applications, where we have to deal with detailed and large-scale datasets, often coming from a variety of sources ranging from traditional CAD modelling to 3D scanning. The aim of this research position is to
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model without sharing their personal data; FL reduces data collection costs and protects clients' data privacy. In doing so it makes possible to train models on large datasets that would otherwise have
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Seppelt, Director of the Luxembourg Centre for Socio-Environmental Systems (LCSES) Email: Your profile The successful candidate will apply modern data science techniques, including the analysis of large
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transcriptomics) opens new research horizons on cancer pathologies. These data, of very large dimensions and volume, bring new methodological challenges in terms of statistical and mathematical analysis, as
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learning, focusing on identifying abrupt shifts in the properties of data over time. These shifts, commonly referred to as change-points, indicate transitions in the underlying distribution or dynamics of a
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huge data storage capacity to accelerate the research performed in intensive computing and large-scale data analytics (Big Data). This characteristic distinguishes the HPC center at the university from
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live in. Your role The CLAIM and ICR groups are seeking an outstanding postdoc to strengthen their research teams with expertise in Large Language Models, more precisely in Agentive Reasoning and LLM
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research work will be to devise efficient algorithms for source separation in DAS measurements. Issues such as large data volumes that can exceed 1 To per day and per fiber, instrument noise, complex nature
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through text, images, networks, … A similar situation can be encountered in the context of medical data, where the data types may be even more large. It is therefore of strong interest to be able to analyze