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processing, quality control, integration, and analysis of single‑cell and multimodal omics datasets (e.g. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell
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Europe Marie Skłodowska-Curie Actions Doctoral Network (MSCA DN) COMBINE. The successful candidate will undertake research on: Deep learning for solidification in multiphase flows with radiative heat
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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investigate deep learning architectures capable of learning microstructure-property mappings, including convolutional neural networks for microstructure image analysis, graph-based representations
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France 91120, France [map ] Subject Areas: Applied Mathematics - statistical learning, deep learning, AI for mathematics, AI for Science Appl Deadline: 2026/03/24 03:59 AM UnitedKingdomTime (posted 2026
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: Microbiome; Bacteria; Microbiology; Metabolites; Nuclear Magnetic Resonance, Mass-spectrometry, Chemometrics; Multivariate statistics; Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL
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candidates in the area of Business Analytics, with particular interest in those applying machine learning and deep learning methods to business domains, such as HR analytics, marketing analytics, and
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for architecting Northeastern University's transition from legacy data structures to a modern, scalable, AI-ready data architecture. This role conducts deep assessments of existing systems-including Banner, Workday
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the Job which include, but are not limited to, Computer Vision, Deep Learning, Federated Learning, and Cloud Computing. Desirable: B1 A comprehensive and up-to-date knowledge of current issues and future