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Multidisciplinary geophysical time series analysis for a new monitoring approach in a multi-hazard environment based on an innovative and dense network deployed near an active fault: the Alto Tiberina case study
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alarms in bedside monitoring. The ideal candidate will leverage their experience with complex data analysis, in particular time-series data analysis, biomedical/clinical informatics, and/or signal
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to the following: SDSC6012 – Time Series and Recurrent Neural Networks SDSC6016 – Predictive Analytics and Financial Applications SDSC8013 – Statistical Methods for Categorical Data Analysis (For detailed course
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amount corresponds to 1.309,64€ according to the table of scholarships awarded directly by the FCT, I.P. in the country (https://www.fct.pt/apoios/bolsas/valores ). The period of payment of the scholarship
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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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on hormonal time series data collected at unprecedented time resolution in healthy humans and in patients, including studies in real life settings with a state-of-the-art wearable device (https
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accumulate genetic and epigenetic changes that fuel somatic evolution through drift and selection. Over time, these processes turn tissues into molecular mosaics containing competing subclones, often carrying
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31 Jan 2026 - 00:00 (Europe/Madrid) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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by Institut Pasteur, the objective is to continue calibration and sensitivity analysis, and to assess the model's transferability to other Southeast Asian metropolitan areas for which vector time
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tools for assessing structural behaviour, identifying damage, and predicting failures, using computational simulation and time series analysis techniques. •Contributing to the experimental validation