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Field
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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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that generate code (Vaithilingam et al. 2022). However, current AI-generated code often contains errors and lacks scalability, requiring manual debugging and refinement. While AI can produce valid snippets, it
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influence of pulsed or continuous currents on PPBs during flash sintering. Finite Element modeling using the Abaqus software and a multiphysics framework will be employed to quantify the processes occurring
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Description: Accurate battery State of Health (SOH) estimation is vital for electric vehicle safety and longevity. Current models often fail to balance accuracy with computational efficiency. Collaborating with
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calculations will be. The mathematical model will be defined based on the shape of the heat source and the heat flow density. At the same time, it is essential to consider the thermophysical and mechanical
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process modelling, See further information at https://endure.dtu.dk/ and https://cordis.europa.eu/project/id/101227649 . Responsibilities Your overall purpose will be to develop, model, and validate a
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Project is being carried out within the First Team FENG programme of the Foundation for Polish Science Project description: 3D object generation is currently one of the most important trends in computer
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-ON-BRAIN (https://cordis.europa.eu/project/id/101227124 ) Project Reference: 101227124 Application deadline: 15/05/2026 Position Overview One PhD position is available in the µOrganoLab at the Institute
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into actively morphing and efficient structures? Applications are invited for a 3.5-year UK PhD studentship for the project "Design, Experimental Investigation, Aeroelasticity Modelling and Control of an Aircraft
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resilience to current and future forest disturbances and assess the implications for forest ecosystem service supply. The main methodological approach applied will be forest landscape simulation modelling