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extensive expertise in technology and systems for sustainable production of food and bioenergy, including optimal nutrition circuits and logistics systems. Within the field of methodologies, we have extensive
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spray pyrolysis to produce the nanoparticles and we will study in detail their physicochemical properties. We will link these characteristics to the achieved drug loadings and optimize the nanoparticle
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and verification of computation technology for model-based analysis and optimization of process systems, in this case systems for managing stormwater in extreme situations. The work is carried out in
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approach that integrates wireless communication, computer vision, and machine learning to optimize PC transmission from sensors to an edge server for remote registration. The research is funded by Wallenberg
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Applicants must have: PhD degree obtained, doctoral thesis in Biology Completed postdoctoral training Excellent proficiency in English, both spoken and written Practical and theoretical experience in
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an individual research project, you will be responsible for setting up and evaluating data analysis, implementing models and networks, define optimal scientific protocols, and write scientific articles and
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-dimensional statistics, and optimization. Documented experience in working with biological data, especially genomics, or other types of high-dimensional data such as imaging. Excellent programming skills in
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: detailed theoretical studies and optimization of light guidance in HCFs, characterization of fabricated HCFs (on both structural and optical transmission properties), experimental investigations of material
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optimization • Experience of multidisciplinary work and collaboration between academia and external partners. • Good programming skills in Python (Pytorch) etc. • Additional knowledge on waste and Near-infrared
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artificial intelligence), exploring future skills, and optimizing equipment management. You will work in close collaboration with major industry partners to collect and analyze real-world empirical data using