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possible for up to 1 day/week. You will join an interdisciplinary team of researchers spanning imaging science, machine learning, genetics, and population health, working closely with collaborators
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
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platforms include GRO-seq, RNA-seq, ChIP-seq, ATAC-seq, CRISPR-seq, single-cell RNA/ATAC-seq, microC, machine learning, sophisticated mouse genetic tools, and an ex vivo tissue culture system from patients
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to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and predictive analytics Good communication skills and
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of Science at Radboud University . The Data Science Group comprises around 50 researchers with expertise in machine learning, information retrieval and other specialisations that are important in working with
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the LAMP group at the Computer Vision Center (CVC), in Barcelona, Spain. The position is for 2-3 years and linked to the project “Foundations for Adaptive and Generalizable Deep Learning” (EXPLORA
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Requirements Applicants must hold a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, or a closely related field. A strong research background and programming experience
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the next generation of secure agentic AI systems through cutting-edge research in adversarial machine learning and formal verification. The Role As a research scientist, you will contribute to frontier AI
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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, statistics, or mathematics OR a strong background in gene engineering and functional interrogation of hematopoietic stem and progenitor cells. Strong knowledge in bioinformatics, machine learning, statistics