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Field
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analysis algorithms will be used to assess how different neutrophil subpopulations directly and indirectly kill tumour cells, and how this behaviour is influenced by other cells in the tumor microenvironment
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms. Assist with organizing large-scale multimodal neuroimaging dataset, brain
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P2S2 project aims at developing parton-shower algorithms with unprecedented (logarithmic) accuracy for jet substructure at the LHC. The project also has connections with analytic resummations and studies
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, chemical fixation and resin embedding, FIB milling, cryo preparation) Experience in developing and using correlative workflows, data processing and data visualisation, including methodologies and algorithms
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/transformative innovation to help develop innovative EO solutions. We offer: a stimulating multinational, interdisciplinary and open work environment; access to high-performance computing infrastructure and
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machine learning, statistics, or applied mathematics that could drive the frontier of biomedical research. The role will be focused on the development of novel computational and algorithmic methods, with a
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of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en
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control (MPC) under uncertainty for autonomous systems. The research aims to develop state-of-the-art numerical methods for solving challenging belief-space optimal motion planning problems and their
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Position Summary The postdoctoral fellow will develop artificial intelligence applications to support characterization of medical data with a focus on radiology image, radiology reports, and
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long ride, but a ride worth taking! Key Qualifications: Deep knowledge about how biological neurons have been trained before, and new ideas on how to train them Prior knowledge and experience in encoding