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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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fundamental and applied research in different areas of Human-Computer Interaction (HCI) such as visualization, human-centered design, privacy, graphical design, and human-centered AI. We are looking
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. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice or other forms
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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to the application deadline. PhD in computer science, electrical engineering, biomedical engineering, or a related field. Experience in Python programming, natural language processing, and multimodal deep learning
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Source (ESS), Sweden, the European Molecular Biology Laboratory (EMBL), Institut Laue-Langevin (ILL), France, the International Institute of Molecular Mechanisms and Machines, (IMOL), Poland, and the
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classification and multi-layered environment mapping -Digital twin generation for natural environments -Semantic scene-understanding in natural environments for robust decision-making -Learning-based
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teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. Your primary focus will be on conducting high-impact
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The postdoc fellow will conduct research in the intersection of AI/Machine Learning and Software Technology. The advertised position will be placed in the DISTA research group (https://lnu.se/en/dista
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facilities that are highly aligned with the goals of the project. Who we are looking for We seek candidates with the following qualifications: To qualify for the position of postdoc, you must have a PhD degree