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. This project will involve applying and evaluating statistical and machine learning models for data integration and interpretation. A strong foundation in statistical modeling will be essential for applications
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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. Located in
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foundation in computational or statistical genetics. Experience analyzing large-scale datasets is essential, as the work will involve complex genomic and multi-omics data. Familiarity with machine learning
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The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark invites
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark invites
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. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. This program
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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to advancing machine learning in biomedicine. The Program focuses on developing and applying cutting-edge AI approaches to address key challenges in molecular biology, clinical research, and translational