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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 10 days ago
information, as well as an analysis chain to instantiate and use models on open-source and industrial case studies. Outcome The project will propose a methodology to realize code migration of a niche technology
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scientific methods, often in conjunction, including qualitative data collection and analysis via semi-structured interviews, structural micro-econometric modeling and estimation, and statistical analysis
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, contributing to the development and maintenance of FlaGs and its web server for comparative genome analysis, developing Python-based tools and code for retrieval and processing of publicly available genomic data
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of regulatory T cells isolated from various tissues under pathologic conditions 3) Analysis of the functionality of regulatory T cells Where to apply Website https://pica.cineca.it/ Requirements Additional
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7 Apr 2026 Job Information Organisation/Company Ecole Centrale de Lyon Research Field Computer science » Informatics Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage
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. This position is ideal for someone interested in clinical research, health data analysis, or digital health applications, and who wants hands-on experience working at the intersection of clinical medicine and AI
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data, preparing statistics, making recommendations based on research findings, and monitoring and coordinating project/program activities. This position is governed by state and federal laws and
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to clean and organize incoming JHHCC and CNICS data. Identify potential problems with study data and collaborate with data managers to resolve issues. Read concept sheets and draft statistical analysis plans
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FieldHistory » History of scienceYears of Research ExperienceNone Additional Information Eligibility criteria The candidate must hold a PhD degree in the field of analysis (theoretical and/or numerical) of PDEs
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science, industrial engineering, or a comparable field (Master’s degree) Knowledge of modeling, optimization, and data analysis of energy systems Interest in electricity markets, energy system analysis, and model-based