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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
fields Experience with image analysis, or computer vision Good knowledge of basic machine learning techniques, such as variational autoencoder Good presentation and writing skills Proactive, independent
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Technology » Computer technology Technology » Communication technology Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 4 Oct 2026 - 23:59 (Europe/Oslo) Country
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project, an interdisciplinary and transdisciplinary research project funded by NWO, the Netherlands Research Council, under the call on KIC Consumer behaviour for a circular system transition. See: https
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong
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computer vision applied to healthcare; developed within ongoing projects and other future projects in related areas, as well as the pursuit of new funded projects and support for laboratory management at CIR
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of intangible cultural heritage Experience in integrating computer vision and NLP approaches for multimodal cultural heritage applications Strong research and analytical skills, with experience in data collection
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nanocrystals, hybrid perovskites and 2D materials. Development of new data-driven approaches for studies of optoelectronic properties using EM, including machine learning / machine vision algorithms. The balance
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Internet of Things (IIoT) Sensor Fusion and Localization Embedded Systems and Edge Computing Computer Vision and Intelligent Navigation Experience in one or more of the following would be advantageous but is
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learning, computer vision, or a related field; knowledge of affective computing, generative AI models, and deep-learning methods; proficiency in Python and experience with machine-learning libraries
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vision, numerical analysis and computing as well as probability and statistics. What you bring Master’s degree in mathematics or equivalent, including a solid background in analysis, dynamical systems, and