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information is lost through this depreciated sampling frequency remains unknown. DETERMINER aims to determine the optimal sampling frequency for detecting externally driven phytoplanktonic change while also
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, a large initiative funded by the Danish Ministry of Foreign Affairs and managed by Danida Fellowship Council. Ethio-Nature aims to optimize the use of machine learning and remote sensing to site
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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optimization and validation and in addition, we aim to discover novel VHHs capable of crossing the blood-CSF barrier and delivering therapeutic cargoes to the brain. You will become an integral member of a
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improved patient outcomes Integration of findings into translational research, collaborating closely with clinicians, imaging specialists, and bioinformaticians to optimize interventional oncology treatments
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. The HEXAPIC project aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimizing PIC algorithms
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immunohistochemistry. Flow cytometry and cell sorting. High-throughput screening approaches. Development or optimization of molecular methods. Postdoctoral scholarships may be established for foreign researchers who
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Testing and Experimentation Facility (TEF) for the energy field. Specifically, it leverages AI and cutting-edge infrastructure to optimize EV charging and energy systems. By integrating distributed energy
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research questions. This postdoctoral scholarship offers the opportunity to be a part of this AI revolution by developing novel neural network architectures specifically optimized for plant genomic data. Our
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learning paradigms as well as interactive data- and model exploration with domain knowledge towards optimal performance in real-world generalization scenarios. AqQua is a large-scale collaborative research