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format. This will allow combinations of neural networks with physics models. The project brings together PhD students and senior researchers from multiple disciplines to tackle challenges in sustainable
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At the Faculty of Engineering and Science, Department of Materials and Production a position as PhD stipend in Muscle Neuromechanics and Ultrasound Imaging, within the doctoral programme Materials
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and prosthetic devices in the real-world. This PhD project offers the opportunity to work on pioneering research that combines state of the art computational modelling (deep neural networks) and
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or infrastructure. This is what makes our daily work so meaningful and exciting. The Division of Computational Genomics and Systems Genetics is seeking from October 2025 a PhD Student in Deep Learning for Rare
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University, KU Leuven and coordinated by Hasselt University (Prof. J. Hendriks). The PhD student will be engaged in setting up iPSC-derived human neural (brain) organoid model recapitulating neural-microglia
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and prosthetic devices in the real-world. This PhD project offers the opportunity to work on pioneering research that combines state of the art computational modelling (deep neural networks) and
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, accurately and securely. Goal of this PhD project High-capacity neural models, such as transformers, have been pivotal for establishing general-purpose models for a wide variety of natural language tasks
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careers in the language sciences. Our education and training program involves both core and individually chosen coursework to complement the PhD research, and training in soft skills such as writing and
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The Max Planck Institute for Neurobiology of Behavior – caesar • | Bonn, Nordrhein Westfalen | Germany | 4 days ago
not required to be admitted, but German language courses are offered for free for interested PhD students. Full-time / part-time full-time Programme duration 8 semesters Beginning Only for doctoral
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Vacancies Two PhD positions on Flexible and User-adaptive statistical inference Key takeaways You will develop a mathematical framework for multiple testing, enabling flexibility in study design