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Field
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programme investigating early lung fibrosis at King’s College London. It is anticipated candidates will have a relevant PhD in immunology or respiratory sciences, and have experience with cell culture
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Description of the offer : We are opening two positions in the field of “Metallic and Oxide Materials for Orbitronics and Magnonics” at Institut Néel, CNRS, Grenoble The first position (PhD
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Computer Science Department at Princeton University. We seek candidates with computational biology, bioinformatics, computer science, machine learning, statistics, data science, applied math and/or other
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) information-theoretic active learning, and c) capturing uncertainty in deep learning models (including large language models). The successful postholder will hold or be close to the completion of a PhD/DPhil in
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to: designing, implementing, and optimizing high-performance C++/C# software modules for real-time control, sensor fusion, and data analysis; developing unity‐based visualization and user-interaction interfaces
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the possibility of renewal subject to funding availability and satisfactory performance. Applicants should possess a PhD degree in Biology or related disciplines, preferably with experience in virology research
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analysis of large data sets Prior experience in signal transduction research Knowledge, Skills and Abilities: PhD level knowledge and understanding of basic cellular and molecular biology Expertise in cell
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of cancer by analyzing and integrating multi-omics and clinical data. Key Responsibilities Analyze and interpret multi-omics datasets, including genomic, transcriptomic, and clinical data from over 7,000
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 4 hours ago
candidate has excellent quantitative and data analysis skills, a proven ability to work independently, and a collaborative mindset. They will be expected to lead their own research projects, contribute
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data