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on methodological development in cryo-electron microscopy (cryo-EM), particularly in image reconstruction and 3D volumetric analysis of macromolecular structures. Rather than aiming to incrementally optimize existing
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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are not limited to: Learn research techniques to develop algorithms and models for the simulation of field data Participate in experimental activities such as research design, data collection, technical
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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by
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research in MAE addresses the immediate needs of our industries and supports the nation’s long-term development strategies. In the new era of industrial 4.0 and sustainable living, MAE is rigorous in
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• Produce research products such as well-documented algorithms and code, software, and research publications • Prepare results for publications, work with collaborators in writing publications, and, in some
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positions in the interdisciplinary research environment “Culture and Society” to develop research on themes relevant to the thematic area “Digital Society, Infrastructure, Legacies”. This thematic area
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and leukemias (in particular Hodgkin lymphoma and hairy cell leukemia), and to translate this knowledge in the clinic by developing new precision diagnostic and therapeutic tools (as exemplified by
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autonomous systems. Support development, testing, and evaluation of machine learning and autonomy algorithms. Assist with implementation of software frameworks and data processing pipelines. Provide technical
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. Doctoral studies end with a thesis and a doctoral degree. More about being a doctoral student at LTH on lth.se. Subject description This project aims to develop novel algorithms for Neural Rendering