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machine learning methods. Provide theoretical predictions to guide experiments, and atomic-scale physical understanding to experimental observations. Publishing findings in peer-reviewed journals
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Differential Equations Appl Deadline: 2025/11/03 11:59PM (posted 2025/09/05, listed until 2025/11/03) Position Description: Apply Position Description The research group of Professor Mikaela Iacobelli in
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information and communication theory, machine learning, and signal processing. We offer a dynamic, supportive, and international research environment with around 150 employees from more than 20 countries. Our
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, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced computing resources. The MMD group is responsible
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include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and iterative solvers. Successful applications will work in applications
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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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, machine learning, analysis of unstructured and multimodal data, or advanced quantitative methods and use of AI in communication studies will have an advantage. The appointee will assist in a General
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. Research Themes and Projects: We are an interdisciplinary research team integrating single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine
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preferably start around 01-12-2025 and requires knowledge of geometric image processing and machine learning. Information As Post-doctoral Researcher within VICI Project "Geometric Learning for Image Analysis
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simulations), computational chemistry, machine learning, enhanced sampling methods, force field development, or related fields are encouraged to apply. Start date is flexible. the postdoc will collaborate with