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with modern AI frameworks and APIs for developing agentic applications. Experience with multi-omics integration, gene regulatory networks, spatial transcriptomics, trajectory analysis, or chromatin
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analytics, or network analysis. • Experience in agent-based modeling or simulation is highly desirable. • Demonstrated ability to publish in internationally recognized peer-reviewed journals
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Develop novel methods and algorithms for the verification, testing and robustness analysis
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the research themes of software engineering, engineering computing, sensor networks and measurement technology, grid computing and physics data analysis, machine learning, and interactive and collaborative
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computational chemistry, reaction network analysis, and machine learning for organometallic catalytic reactions. 2. Design of membrane-permeable macrocyclic peptide drugs via machine learning structure
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articles and policy-related samples, such as a policy memo, briefing paper, analysis, report, or similar document, are preferred. This is a 20-month, full-time, term-limited appointment. This position
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. Knowledge of cybercrime concepts and LLM prompt techniques. Proficiency in programming languages such as Python, C/C++, and Java. Familiarity with vulnerability analysis, network analysis, and cybercrime
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define how the choroid plexus develops, communicates with the developing brain and responds to maternal immune activation. The successful candidate will lead the computational analysis of large-scale
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, epigenomics, nucleomics, etc.) Multimodal spatial and single-cell data visualization 2D and 3D bioimaging data visualization Data analysis and data management infrastructure for biomedical data visualization