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project is to develop a high-performance computing framework for mass spectrometry proteomics to enhance efficient processing and interpretation of large datasets using deep learning algorithms and GPU
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in signal processing and control. Your role and goals As a researcher in this project, you will work on mathematical models for describing the radio environment and to design algorithms for estimating
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, AI, and other algorithmic techniques in qualitative social scientific research. In line with the interdisciplinary and reflexive ethos of DIVSOL, attention to the societal implications of AI is an
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embodied and justice-oriented approaches to datafication literacy, to support human agency and mitigate algorithmic harms. The focus will be on empirical research that uses different design and game-making
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on sustainable electronics materials and fabrication processes, flexible and stretchable electronics, self-powered sensor nodes, and heterogenous integration. We are excited to announce an opening for a motivated
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reconstruction, semi-supervised semantic labelling of 3D environments, sensor fusion, and modelling of dynamic environments. The doctoral candidate will also be involved in dissemination through social media
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, electronic circuit design characterization techniques (Raman microscopy, AFM, SEM, etc.) neuroscience biological/in-vivo sensors Experience in collaboration with biologists or medical researchers is an
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RF sensors and antennas, and we are developing unique radio head with CMOS technology for these applications. Your experience and ambitions Candidates should possess basic skills in integrated circuit
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that are of practical interest. The postdoctoral researcher will contribute to the theoretical foundations of inverse problems involving wave phenomena, develop cutting-edge computational algorithms, and apply
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such as earth with different sizes of rocks. 2) Development of advanced control algorithms integrated with force and loss models to prevent overloads and hazardous situations, ensuring operational