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dynamics and heat transfer research. Programming skills in Python and MATLAB, particularly in machine learning, data analysis, and image processing. Experience working in Linux environments. Ability
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world-leading research environment through the development of paradigm-shifting knowledge about bio-based wood adhesives in three research areas: raw materials and formulations, aspects of adhesives, as
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: The position demands a technical background in and skills related to: Detailed characterization of materials (morphology and microstructure by optical & scanning electron microscopy, image analysis
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of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming. Development of advanced imaging and
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techniques • Explainable AI/ML using visualization • AI/ML-empowered visual analytics of multivariate networks (network embeddings, …) • Large Language Model (LLM)-assisted visual analytics of text, images
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scale. Characterization of ash interactions with products. Imaging and determination of chemical composition with SEM-EDX. Advanced image analysis for quantification of porosity. Multicomponent chemical
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a focus on visual language grounding, in other words, the linking of elements of natural language (words, phrases, or sentences) to visual inputs (such as images or video) in a meaningful way. The
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scale. Characterization of ash interactions with products. Imaging and determination of chemical composition with SEM-EDX. Advanced image analysis for quantification of porosity. Multicomponent chemical
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(transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional
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. Development of advanced imaging and characterization technologies (X-ray micro tomography, EPR imaging and spectroscopy) to evaluate performance of electrodes and to map electrolyte chemical composition in