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an obtained doctoral degree. The successful candidate will work in a team dedicated to developing and using new approaches and methodologies for seismic imaging and Full Waveform Inversion using Generative AI
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at the intersection of machine learning, bioinformatics, and computational pathology. Project Overview: Integrating histopathological imaging with omics (e.g., transcriptomics, genomics, proteomics) holds tremendous
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, please see DTU PhD Guide . The assessment of the applicants will be made by Associate Professor Kaushik Das, Senior Researcher Matti Koivisto, Postdoc Rujie Zhu and Head of the RES section Gregor Giebel
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, catalysis studies - in particular electrocatalysis and Python programming Experience within the following fields is highly beneficial: Transmission electron microscopy, Electrochemistry, Image analysis, Big
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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FOR We are looking for a postdoc to join the Department of English and American Studies with focus on linguistics and L2/Ln acquisition. MAIN JOB CONTENT Independent performance of specialised research and
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initiatives at SWIMS. The ideal candidate will have expertise in IoT, sensor development, ecological monitoring, and advanced ecosystem imaging methods such as photogrammetry. The officer will collaborate
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Alex Leung (Mechanical Engineering at UCL) will also collaborate. he specialises in imaging of additive manufacturing and will support the project by assisting with the in-process monitoring. We expect
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lines and cancer tissue samples. Selected candidates will be part of an international team of PhD students and postdocs that works at the forefront of biomedical research. The PhD student will be a member
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immunology is highly advantageous. Proficiency in core immunological techniques such as multicolor flow cytometry, ELISA, tissue sectioning and imaging, or in vivo mouse models is strongly preferred