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to submitting your application, please review and update (if necessary) the information in your candidate profile as it will transfer to your application. Job Title: Post-Doctoral Scholar Department: Medicine
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machine learning. We focus on inductive logic programming (ILP), which learns logical rules from data. We primarily use automated reasoning techniques, such as SAT/ASP/SMT/MaxSAT solvers, to learn rules
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and machine learning. We focus on inductive logic programming (ILP), a form of inductive program synthesis which learns logical rules from data. The focus of this position is to develop ILP/program
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, analyze data, and interpret results. -Publish research findings in peer-reviewed journals and present at professional meetings. -Assist in writing grant proposals to secure external funding. -Oversee and
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screening, and multi-omics data to uncover cancer vulnerabilities and enable next-generation therapeutic target discovery. The group is supported by major competitive funding, contributes actively
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candidate will conduct numerical simulations, develop and implement computational methods to interpret complex data, and contribute to the preparation of grant proposals, progress reports, and peer-reviewed
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up experiments • Collect and analyze soil, water, mineral, and wastewater samples • Use analytical equipment or work with data from analytical equipment (e.g., ICP-OES or ICP-MS, XRD, FTIR, EA, EA-IRMS, etc
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-culture organoid assays, and in vivo models to decode the mechanisms underlying CAF-driven CRC evolution. Access to single cell RNA sequencing and spatial transcriptomics data from active clinical trials
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expression, gender identity, genetic information, national origin, race, religion, sex (including pregnancy and pregnancy related conditions), sexual orientation or military status. Duke aspires to create a
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, data collection and analysis, and utilizing collaboration tools and AI technologies. Why Apply? Gain exposure to world-class research, data analytics, and artificial intelligence applications within OP