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testing code, and learning from feedback. 🔍 Research Objectives Design an Agentic SWE Framework Model an AI system that combines reasoning, planning, and self-correction for software engineering tasks
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cohorts of autoantibody-positive at-risk of T1D subjects, a model integrating plasma levels of circulating microRNAs with clinical variables (glucose/C-peptide responses, autoantibodies, HbA1c, BMI SDS
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robust inference even when data are scarce or uncertain. The project will also explore surrogate modeling approaches for the rapid approximation of solutions to complex differential problems. These models
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proficient in process design, characterization, and modeling of low carbon electricity generation technologies that ensure access to affordable, reliable, and sustainable power for all. We seek candidates with
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planning, and explainable decision support. The PhD will operate across two worlds: The University of Twente — advancing scientific models, algorithms, and hybrid AI methodologies; Thales (the industrial
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models using induced pluripotent stem cell (iPSC)-derived kidney organoids. A key aspect of this work will involve integrating bioprinting and organ-on-chip technologies to create mature and
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the battery and propose design and operational strategies to overcome them. A core feature of your work will be combining multiphysics modelling for cell design with electrochemical testing, e.g. charge
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. Writing scientific articles. Presenting results at scientific conferences. Where to apply Website https://sede.uam.es/sede/piproyectos Requirements Research FieldBiological sciencesEducation LevelPhD
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measurements Calibration of materials as sensors to measure temperature, oxygen, and pH values in cells Development of models based on artificial intelligence algorithms to interpret luminescence signals Study
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of emissions of greenhouse gases. The reason for most of this uncertainty is that clouds are especially challenging to represent in numerical models of the atmosphere. Clouds affect the Earth’s radiation