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. scRNA‑seq, scATAC‑seq). Train, evaluate, and benchmark deep learning models operating on single‑cell, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating
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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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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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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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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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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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the development, evaluation, and practical application of machine learning methods (especially deep learning) Publication of scientific results in renowned international journals and conferences Teaching of courses
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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
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(PyTorch, scientific Python) with solid experience in scientific computing and software development; familiarity with C++ and Linux environments is an advantage Strong background in deep learning for image
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bioinformatics for immunology research programs. You'll work at the cutting edge of AI-enhanced immunology, applying deep learning, foundation models, and advanced machine learning approaches to understand how