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Field
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fusion for autonomy. Digital Twin & Edge Computing: Implement real-time synchronization and analytics. IoT Integration: Design and manage data acquisition from sensors and UAVs via embedded systems
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opportunity to understand the disease. We are looking for investigators with expertise in Whole Genome and Exome data, colocalization, Mendelian Randomization, and TWAS/Fusion approaches to lead our effort to
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with embedded real-time systems are desired. This position will carry out research on sensor fusion, perception, and control of autonomous vehicles for different applications such as transportation
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opportunity to understand the disease. We are looking for investigators with expertise in Whole Genome and Exome data, colocalization, Mendelian Randomization, and TWAS/Fusion approaches to lead our effort to
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optimization. We are particularly interested in a) developing novel AI methods for analyzing pathology data, b) multimodal data fusion strategies, c) development of computational methods for rare diseases and
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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transformer architectures for multimodal fusion (RGB + thermal, intraoperative video, OR signals, EHR, surveys); develop temporal and cross-attention components for longitudinal risk trajectories. Build robust
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2025/11/13, listed until 2026/02/28) Position Description: Apply Position Description The Institute of Theoretical Physics at the Chinese Academy of Sciences (ITP-CAS) (http://english.itp.cas.cn ) is
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Sciences at the University of Amsterdam (UvA). BDA works on the development of methodology for data mining, machine learning/deep learning, data fusion, and modelling and application of these methods
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Intelligent Control Systems RESPONSIBILITIES Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis