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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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Artificial Intelligence (applied mathematics, computer science, etc.), or a thesis defense scheduled for 2025. • Research contributions in deep learning, statistical learning, natural language processing (NLP
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the climate system and have all been identified as large scale tipping elements, albeit on very different time scales. While for each of these tipping elements critical thresholds remain matter of active
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Ine-Therese Pedersen 15th August 2025 Languages English Norsk Bokmål English English PhD position in Deep Learning for Metocean Data Apply for this job See advertisement About us We are announcing a
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the molecular level. While structural predictions using deep learning methods like AlphaFold have revolutionized our understanding of sequence dependent molecular structure, we currently have much more limited
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: You will be responsible for the sensor system and the perception algorithms of an autonomous mobile robot. You will engage in research around deep learning and 2D/3D computer vision for a well-defined
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effect can be predicted. You will acquire in-situ and remote-sensing data of cirrus forming downwind of flights over the past decade, along with measurements/estimates of local conditions and emissions
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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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deep learning methods to enhance the predictions beyond existing data. By incorporating microstructural features into predictive models, the aim is to create a reliable data-driven modelling framework
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to frailty assessment could be beneficial. Manual measurements from CT scans, however, are labor-intensive and subject to observer variability. The advent of deep learning in medical imaging presents a