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Field
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the VILLUM FONDEN. The overall aim of the project is to introduce microstructural engineering to the field of additive manufacturing (AM) of metals. This is to set the stage for optimizing metals
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Research Infrastructure? No Offer Description Chromatographic problem solving, commonly referred to as method development, is hugely complex, given the many chemical parameters that need to be optimized and
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for cryo-electron microscopy (cryo-EM) data analysis, modeling conformational heterogeneity, and identifying optimal binding candidates, by integrating image analysis and docking across multiple structural
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meters. These instruments produce large amounts of data that require several processing steps before the relevant physical variables are obtained. Typically, machine learning methods are used to optimize
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further latency. Crucially, current MRI systems lack any form of predictive intelligence that could inform optimal configuration ahead of, or during scanning. The Computer Engineering (CE) section
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innovative projects that have a major impact on society. Context and contributions of the position: Understanding subsurface fluid flow is crucial for optimizing geothermal systems and mitigating risks such as
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efficient and sustainable chemical processes for the production of active ingredients in the pharmaceutical and agrochemical industries. You will develop flow and microfluidic reactors for simultaneous
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drilling, drilling technology, thermomechanical processes, and AI‑driven drilling optimization, as described in the project outline. Develop and apply numerical, analytical, and data‑driven models
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on brain cancer cells. Cancer cell microtubules have large electric dipole moments and are influenced by a process in which an electric field can affect the way in which the dipoles organize themselves in
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for the turbomachinery design optimization process conducted by a parallel PhD student at LMFA. The numerical solver involved is ProLB. It is an innovative Computational Fluid Dynamics (CFD) software solution developed