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at system level. In this PhD project, you will develop the measurement and analysis methods needed to make these environments observable. You will design and validate a cost-effective, synchronised multi-node
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-europass-cv ) Analysis of the challenges associated with industrial heat decarbonisation and the potential of innovative IHTHPs to address these challenges, including the needs for technology development
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
the sensitivity and uniqueness of information used to express user intent, and estimating the consequences of data leakage, including re-identification risks. Sensitive data-flow analysis: tracking how personal and
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debiased machine learning Heterogeneous treatment effect estimation Longitudinal and survival analysis Propensity score methods and overlap weighting Transportability and generalisability Sensitivity
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Digital manufacturing, Industry 4.0, or cyber-physical systems o Product design for disassembly, remanufacturing, or recycling o Data analysis, AI, or machine learning applied to engineering systems
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, and the integration of compliance requirements into decision-making structures. It will combine doctrinal legal analysis with case studies and design-oriented methodologies in order to develop
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data can be captured through IoT technologies, and how this real-time information can support process analysis, redesign, automation, monitoring, and decision-making throughout the BPM lifecycle
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Fundacio de Recerca Clinic Barcelona-Institut d'Investigacions Biomediques August Pi i Sunyer | Spain | 7 days ago
, or bioinformatic analysis will also be considered an asset. Previous international research experience and participation in mobility programmes will be positively valued Research group: Translational research in
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neuroscience and evolutionary biology. The University of Groningen provides exceptional infrastructure, including access to the Hábrók high-performance computing cluster for large-scale data analysis, large
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, annotators, and underlying neural architectures. The ultimate goal is to produce argument mining tools that are more robust, generalizable, and fair, applicable to sensitive domains such as the analysis