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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
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modeling and AI. This position will include: Developing new Generative AI algorithms for developing intelligent agents in areas such as planning, exploration, perception, physical reasoning, and memory
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settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide and mentor graduate students and other junior team members working on the project
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* Design, implement, and evaluate wireless-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using wireless sensors. Help guide
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nanotechnology and polymer research relevant to FDA’s public health mission. The Nanotechnology Core Facility supports FDA mission by developing and applying state-of-the-art analytical approaches to understand
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matter expertise supporting the development of new studies, modeling and simulation, and algorithms. The Post-Doctoral Fellow will work along with the Division Chief and research managers in the Nuclear
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 7 hours ago
. The position aims to develop novel algorithms, improve model efficiency and performance, and translate theoretical advances into practical solutions across relevant domains. The Fellow will contribute
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 1 day ago
advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition, and participating in developing standardized computational frameworks for regulatory
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. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated. Strong applicants with backgrounds