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Field
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) Interpretable machine learning for network adaptation. In this thesis, the student will study how interpretable models and explainable learning algorithms could be used in real cellular networks for safe
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biology and bioinformatics, as well as in Machine Learning (including Large Language Models). Good understanding of evolutionary and molecular biology concepts, and good statistical (data analysis) and
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modeling in calculation processes and application of AI techniques for processing dense point clouds Where to apply Website https://sede.uvigo.gal/public/catalog-detail/28364578 Requirements Research
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performance of molecular dynamics studies on molecular diffusion models in membranes. The research is oriented towards the study of the physicochemical behavior of new systems based on paramagnetic ions with
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) - Optimization skills: experience with GAMS or pyomo (or similar), including model formulation. - English: demonstrated ability to write and edit scientific texts in English. Specific Requirements - Quantify
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the framework of the project entitled: “Developing COMPLEX Human ORGganoids to Model and Target Genetic and Systemic Conditions during Congenital Anomalies Of The Kidney And Urinary Tract” (COMPLEXORG
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simulation : Aspen HYSYS/Plus. • Optimization skills: experience with GAMS or pyomo (or similar), including model formulation. • Life Cycle Assessment (LCA): experience with, e.g., Brightway2/SimaPro/Activity
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related field. - Optimization skills: experience with GAMS or pyomo (or similar), including model formulation. - Life Cycle Assessment (LCA): experience with, e.g., Brightway2, Activity Browser or SimaPro
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& Code PID2024-161357OB-I00: Chemosensory systems in bacterial phytopathogens: Unraveling complexity and exploiting novel targets for disease control Principal Investigators: Emilia López Solanilla
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models of spinal cord injury (SCI) to study regeneration and evaluate therapeutic strategies. Project Overview: This PhD project aims to develop and compare humanized in vivo and in vitro models of spinal