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algorithms; experience in 3D/4D (X-ray tomography) image processing; experience in machine-/deep-learning based image analysis; knowledge of tomographic reconstruction methods; experience in materials research
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are seeking a postdoctoral researcher with a PhD in AI-based computational pathology, or related field, with experience in development or application of deep learning methodologies. Knowledge and expertise in
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participating in projects that collect and utilize agronomic data from forages and crop rotations, and (3) writing scientific publications and grant applications. Qualifications: Required: A PhD degree in a
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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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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep
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for materials science, and advanced optimizers for modern deep learning. The research may be conducted in collaboration with the Electronic and Photonic Materials and/or the Computer Vision Laboratory
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, research visits, and other activities to promote a strong multi-disciplinary and international network between PhD students, postdocs, researchers, and industry. Work assignments This position is primarily a
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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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The Department of Zoology is one of the departments within the Faculty of Science and has approximately 80 employees including researchers, PhD students, and administrative staff. Research and