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interdisciplinary, and together we contribute to science and society. Your role We seek a highly motivated bioinformatician or computational biologist who is well versed in the statistical and machine learning
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electricity is supplied from zero or low-carbon sources in 2050, such as renewables or fossil fuels with CO2 capture and storage (CCS). CCS in deep geological formations has consequently emerged as an important
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity
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role in our everyday behaviour. Having a belief seem true involves cognitive phenomenology; experientially taking a belief to be true when we first acquire it and if we later entertain it in thought
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live in. Your role Research related to the following areas: Mathematical statistics, Machine Learning, High-dimensional statistics, Robust estimation methods, Probabilistic foundations of mathematical
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-world applications and labour market needs Support the development of pedagogical content for MOOCs, workshops, and blended learning formats Participate in hackathons, workshops, and AI public engagement
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-quality training and learning materials, and a sustainable plan. FSTM's main tasks are to contribute to the definition of the body of knowledge and competencies, assist in developing the skill tree used as
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, Impresso - Media Monitoring of the Past (https://impresso-project.ch/ ) is an interdisciplinary research project that uses machine learning to pursue a paradigm shift in the processing, semantic enrichment
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found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
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the Institute of Applied Physics in Florence, Italy (IFAC) and to conferences in Europe to present scientific results. Knowledge of inverse methods, statistics or machine learning Knowledge of remote sensing from