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statistical and machine learning methodologies to analyze and predict aspects of the collected data With the guidance of Drs. Stuber and Bruchas, develop experimental methodologies related to two-photon imaging
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related field Strong background in data analysis, particularly with behavior data, functional ultrasound (fUS) or other neuroimaging modalities Proficiency in statistical analysis, machine learning, and
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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Intelligence (AI) and Machine Learning (ML) methods to tackle complex biomedical challenges in nutrition and health. This is a one-year full-time benefits-eligible position that may be extended for up to four
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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streaming and batch processing. These efforts provide the foundation for advanced analytics, machine learning, and AI applications. The IDE Research School guides PhD researchers by offering a platform for
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https://www.academictransfer.com/en/jobs/358104/postdoc-quantifying-gender-ineq… Requirements Additional Information Website for additional job details https://www.academictransfer.com/358104/ Work
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a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the