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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single
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telecommunications networks and urban infrastructures Change: Developing data analysis and modelling methods to understand the interdependency Impact: Better design to enhance telecom and urban performance Job
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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and deep understanding of machine learning, artificial intelligence, algorithms, and knowledge of the latest developments in AI. Proficiency in ML tracking/monitoring tools (MLflow, Grafana) and LLM
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postdoctoral fellows to perform cutting-edge research in AI for radiation therapy. Research areas include developing and implementing AI techniques for image-guided radiation therapy, such as image
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to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields, ultrasound, optics and targeted radiation, microfluidics
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: Python programming Bash programming Familiarity with genomic data Notions of algorithmics Experience with back or front-end web development is a plus Soft skills : team spirit ease in communication
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-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault diagnosis of gas turbines
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environment who will supervise the PhD and collaborating with the rest of the Doctoral Network fellows. Where to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Electrical
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Sete, Languedoc Roussillon | France | 6 days ago
recent decades. Based on time series of lagoon, hydroclimatic and catchment evolution data, analysed retrospectively and with projections to 2050, this thesis aims to determine: 1) the influence of local