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at international conferences. You hold a PhD in computational biology/chemistry, machine learning or a related quantitative field. You have a solid publication record and demonstrated experience with advanced
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and have synergiccollaborationeffects. Weexpect a motivatedearlycareer researcher with stronginterest and experience with GIS/earth observation/climateprojection data as well as machine learning models
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in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field Has strong theoretical and practical experience in deep learning Has hands
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generation Developing and optimizing generative models for de novo minibinder design Integrating structural biology data into AI pipelines for receptor–ligand interaction modeling Fine-tuning large protein
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
workshops. Qualifications Applicants must hold a PhD degree (or equivalent) in a relevant field. Suitable disciplinary backgrounds include but are not limited to: Computer Science, Data Science, Artificial
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analysis and biomedical data analysis, with demonstrated experience in organ segmentation from medical images, using both traditional and machine learning–based methods, and creation of large segmentation
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for physical AI systems that learn and adapt through continuous exposure to multimodal sensory and radio data, and acts upon real-world environment through distributed coordination and control. Emphasis will be
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The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
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geoscientific applications. Current research includes large-scale crop mapping, wetland monitoring, and the integration of machine learning with remote sensing and geophysical data for groundwater mapping. Your
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, Bash). Experience working in a Unix/Linux environment, including setting up and managing High Performance Computing (HPC) clusters. Familiarity with metagenomic data analysis and machine learning