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high-dimensional, dynamic, networked system, applying techniques from machine learning, causal inference, statistics, and algorithms. No prior biomedical training is required—just strong quantitative
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. The successful applicant will integrate multi-modal live imaging and omics data using AI-based pipelines to identify and refine early disease phenotypes, laying the groundwork for therapeutic intervention
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Michael Bronstein, AITHYRA Scientific Director AI and Honorary Professor of the Technical University of Vienna in collaboration with Ismail Ilkan Ceylan, expert in graph machine learning, invites
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group (https://bckrlab.org). We focus on high impact applications and work on knowledge-centric AI and biomedical machine learning including multi-omics integration, single cell analysis, and sequential
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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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and implementation of data systems and analysis platforms with the platform development team (developers, data managers, scientists) Supporting strategic planning and integration of new data modalities