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successfully conducting research as well as postgraduate and undergraduate education within areas such as autonomous systems, complex networks, data-driven modeling, learning control, optimization, and sensor
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systems, complex networks, data-driven modeling, machine learning, optimization, and sensor fusion. The division has extensive collaborations both with industry and other research groups around the
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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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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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principles as well as material properties of extremely thin silica membranes. In this project, you as a PhD candidate will carry out: detailed theoretical studies and optimization of light guidance in HCFs
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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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learning, generative AI, and multi-objective optimization. Evaluate and select design options based on user-defined parameters such as environmental impact, aesthetic value, and cost. Additionally, you will
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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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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