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these images. This project proposes an innovative approach that combines state-of-the-art diffusion models with physical radar knowledge and advanced transfer learning techniques. The methodology incorporates
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The logic and learning (LOL) group is recruiting a postdoc funded by ELLIS institute Finland. You will work with Associate Professor Andrew Cropper . We work on combining logical reasoning and
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computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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, United States of America [map ] Subject Area: Physics / Machine Learning Appl Deadline: 2025/12/02 04:59 AM (posted 2025/09/10 05:00 AM, listed until 2026/03/11 03:59 AM) Position Description: Apply Position Description
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 12 days ago
deep learning (x/f/d/m) Background With the project Deepcloud, we will leverage the machine-learning revolution to understand clouds and their role in the climate system. We aim to train a deep learning
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Molecular Biotechnology (IPMB) of Heidelberg University is offering a 3-year full-time (100%; 39,5 h/week) postdoc position in Multiomics Data Integration and Machine-Learning for therapy response prediction
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation
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The logic and learning (LOL) group is recruiting a postdoc partly funded by the ARC Prize Foundation . You will work with Associate Professor Andrew Cropper . We work on combining logical reasoning
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background knowledge in statistical genetics, machine learning, omics data analysis, and computational biology. Additional knowledge in transcriptomics, statistics, and foundation models is also desired. Fixed
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risk factors. The main objective is to design and apply machine learning and deep learning methods to understand and investigate the functional behavior of gender-specific cancers. The work will include