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The Multiscale Materials Modelling Group at Maynooth University invites applications for three fully funded PhD positions focused on the design of advanced polymer-hybrid anion-exchange membranes using multiscale
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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geomatics, spatial modelling and simulation, and model exploration and evaluation (OpenMole platform https://openmole.org/ ). The recruited individual will also work directly with the project's entomologists
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE MEDICHE VETERINARIE | Italy | about 11 hours ago
1.2, the work will establish a murine AD-diabetes comorbidity model and generate metabolic and cognitive datasets. Objectives include: establishing diabetic models (STZ and HF diet), serial glucose
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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Automation: Develop pipelines and utilities to support data processing, model training, evaluation, and continuous improvement. Collaboration and Knowledge Transfer: Document technical processes, contribute
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model's development. The position is based at LOCEAN on the Pierre and Marie Curie campus of Sorbonne University. The LOCEAN laboratory (https://locean-ipsl.upmc.fr ) is one of nine laboratories in
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psychometric methods to reliably and validly compare children’s, adults' and AI-models’ fluid intelligence across a series of cognitive tasks; and conducting cross-sectional and longitudinal data analysis (e.g
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model integrating subjective, psychophysiological, and behavioral data to clarify the mechanisms underlying PUSM and assess the effects of the biofeedback training Where to apply Website https
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datasets or wildlife imagery Familiarity with data annotation tools and practices for large-scale datasets Knowledge of model deployment and optimization (e.g., ONNX, TensorRT, model quantization) Experience