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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg
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techniques and genomic data analysis. Background in and motivation for genomics or/and biodiversity conservation studies. Strong background in AI/ML fundamentals and extensive experience with deep learning (DL
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and inference of unmeasured observables. 2. Improve computational methods to extract the CKM matrix element Vub from inclusive decays using deep learning approaches. Environment: ICCUB is a María de
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expertise in deep learning and representation learning applied to biological data, experience with large-scale multi-omics datasets (such as single-cell and proteomics), and strong programming skills in
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University Tandon School of Engineering The Dynamical Systems Laboratory at NYU Tandon School of Engineering is seeking to hire a Post Doctoral Associate to work on the mechanics of deep-sea sponges. We seek
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis
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of the following areas: Wireless and satellite communications AI/ML for dynamic networks including Graph Neural Networks, Transfer Learning, Deep Reinforcement Learning, and Transformer-based models
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. The successful candidate will pursue an active research agenda and contribute to the Climate Policy Lab?s ongoing projects, as well as contribute deep expertise in either China, Latin America, or system dynamics
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applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
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to apply. We seek candidates with expertise in some or all the following areas: density functional theory, deep learning, high-throughput simulations, molecular dynamics, and materials chemistry. Strong