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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling
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passive radar to derive forest properties Research subject: Technology Description Microwaves, commonly utilized for radar measurements, interact directly with the underlying material properties
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of new techniques for mass spectrometry imaging and single cell mass spectrometry to reveal chemical processes of importance to biological function and dysfunction. The research group has recently received
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Admission to Doctoral (PhD) Studies in the subject Engineering Sciences with specialization in Biomedical Engineering at the Division of Biomedical Engineering, Department of Materials Science and
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research and methodological development to design and implement novel computational models and solutions. A solid theoretical background and hands-on experience in digital image processing and deep learning
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) classification and utilization based on advanced AI technologies, such as regenerative AI, image processing and reinforcement learning, that can improve the energy efficiency and reduce the operating cost and
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engineering, thermal engineering, or a related field with a strong focus on fluid dynamics, energy systems, heat transfer processes, multiphase flows, or similar areas. A deep understanding of the physics and
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of salt-induced cell clustering will be investigated using genome sequencing, genetic engineering, screening of genetic libraries and/or transcriptomics. Confocal microscopy and automated microbial live
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for Spectroscopic and Acoustic Imaging (https://www.photoacoustics.lu.se/ ). The doctoral student will gain knowledge in optical measurement methods, medical image processing, development of computational models, and
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. Qualifications We are looking for a very motivated and enthusiastic doctoral student who has Competence and skills: -Strong foundation in computer vision (e.g., object detection, image segmentation) and NLP (e.g