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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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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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: 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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. The work is performed in connection to two ongoing research projects “Probabilistic multiscale modelling of the macroscopic crack growth behavior in heterogeneous materials” and “Optimized Digitalization
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community. The fact that you are present and active is something we see as self-evident in order to ensure that you are able to perform your duties in an optimal way and enjoy your working community
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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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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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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
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physiology of tumors, providing a platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional