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a Master’s degree in computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or
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imaging (MSI) is increasingly used to investigate how environmental stressors and micropollutants affect biological systems across space and time. However, data processing, image segmentation, multimodal
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candidate with a background in marine science, biological oceanography, environmental science, data science, computer science or related discipline. Strong analytical, numerical and practical skills are
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particularly important. We welcome candidates from computer science, applied mathematics, physics, engineering, and related disciplines who are interested in combining modern learning methods with
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foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands-on
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: Ongoing master's studies at TU Wien in the field of Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar Good knowledge in computer vision
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, Biotechnology, Bioinformatics, Biology, Computer Science, Medical Technology, or a closely related field. Relevant experience with biomedical imaging, quantitative data analysis, image processing
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processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands-on experience using Python and at
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, Computational Biology, Computer Science, Biomedical Engineering, or a related quantitative discipline Strong background in machine learning/deep learning (e.g., CNNs, transformers, vision models
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extension of results. Collaborate with interdisciplinary teams across multiple institutions. What you bring: Master's or PhD in Computer Science, Applied Mathematics, Physics, Computational Chemistry, or a