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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 17 hours ago
of materials Proficiency in multi-physics FE simulations, topology optimization, and working knowledge of machine learning (ML) algorithms Demonstrated exceptional problem-solving abilities, a passion for
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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 12 hours ago
learning algorithms Strong mathematical foundation specifically in linear algebra, differential equations, and optimization Solid communication and teamwork skills Point of Contact Mikeala Eligibility
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analyses • Lead genomic, metagenomic, and comparative genomic analyses using existing or newly-generated datasets • Develop and optimize laboratory protocols (if applicable) and help train and mentor new lab
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system optimization for remote construction. This position will focus on advancing research in construction assembly science and technology, logistics optimization, and real-time communication frameworks
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Engineer (RSE) who can contribute directly to the core of Dataspaces (written in C/C++) and support the integration and deployment efforts including containerization, automation, and system-level optimizations
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optimization under uncertainty, constrained query evaluation, or the design of efficient, explainable, and scalable query engines. The successful applicant will help design and build novel systems and algorithms
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, safety, and compliance. Perform preventive maintenance on laboratory equipment to keep them in optimal working condition. Conduct experiments related to identifying metabolites in plant and biological
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(toliaslab.org (link is external) ), Tirin Moore (moorelabstanford.com (link is external) ), and other collaborators at Stanford. Role & Responsibilities: Design and optimize large-scale electrophysiological and
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qualified Postdoctoral Research Associate. The incumbent will join a collaborative team to combine synthetic magnetosome biogenesis and computationally optimized cobalt-binding peptides to enable efficient
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run