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Field
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respectively, we seek highly motivated candidates to develop innovative methodologies for radar sounder data processing, with a strong emphasis on artificial intelligence and deep learning. The research activity
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segmentation, target detection and change detection along and across multiannual series of data. Methodologies like foundational models, machine learning, deep learning, multitask learning, enforcement learning
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, etc.), experience in evaluation of algorithms and in Deep Learning libraries. Excellent command of written and spoken English (subject to TU Delft eligibility criteria). To thrive as a PhD candidate
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employment. Starting date: 09.04.2026 Job description:PhD Position: Deep learning for phase-contrast synchrotron X-ray tomography Reference code: 987 - 2026/WP 1 Work location: Hamburg Application deadline
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, with a particular focus on identifying and characterizing rare endosomal escape events. The tasks include developing, training, and validating deep learning–based models for event detection and vesicle
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, and deployability of deep learning models on resource-constrained edge platforms. The PhD candidate will collaborate closely with international project partners and contribute to advancing next
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prediction to process optimization. The focus of this PhD project is to develop and apply machine learning methods across three interconnected tasks: 3D microstructure characterisation. The student will
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. Following an offer of employment, the successful applicant will enroll in the CBS PhD School. Further information about CBS PhD scholarships and the PhD programme can be found at https://www.cbs.dk/en
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Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale. As an early member of this fast-growing team, you will have a unique
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 18 days ago
dynamics data and advanced graph-based deep learning models to decode long-range communication pathways within macromolecular complexes. The PhD candidate will play a central role in this effort by