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Field
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. The successful candidate will pioneer new algorithms for graph-structured data, revisit classical graph problems through the lens of modern machine learning, and help define the next generation of generative
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algorithms into the real development progress Preparing academic publications such as patent applications and research papers Contributing to quarterly and annual report writing and presenting Job Requirements
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-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel algorithms for: Fine-grained video understanding Concept learning Temporal
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RNA-seq, genomics and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are not available or are not adequate. 2.) Apply
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differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic Qualifications Candidates are required to have a doctorate or terminal degree in Computer Science
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point cloud techniques for geometric analysis; (b) develop and implement algorithms for 3D perception; (c) design and execute experiments to evaluate validate and refine algorithms and systems; (d
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algorithms for automated driving. You could also develop your own research portfolio by supervising MSc individual research projects aligned with the Centre’s research themes. You will be expected
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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on integrating an agentic platform for electrocatalyst discovery and developing novel machine-learning algorithms (e.g., reinforcement learning) for materials discovery and process optimization. The candidate will
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 2 months ago
algorithm performance. You will analyze assignment data from December 2025 to the present to identify workload distribution patterns and refine the algorithm using mathematical modeling, programming, and