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Field
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of morphing drone prototypes by combining structural optimization, lightweight design, and experimental testing. The research assistant will: Participate in CAD/CAE modeling and structural optimization of UAV
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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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established protocols and contribute to the design and optimization of new experimental protocols and workflows. In addition, the candidate will be responsible for the maintenance and servicing of critical
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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adaptive systems that jointly optimize morphology and control for real-world physical interaction. Requirements Ph.D. in Computer Science or a related discipline. Strong background in Machine Learning
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perturbation models across diverse single-cell datasets Collaborate closely with Helical-AI on scaling, optimization, and integration of the developed models within an HPC-enabled industrial pipeline Publish
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Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine Learning, addressing challenges
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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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modeling, control, and optimization of power and energy systems with applications to maritime and coastal infrastructures (e.g., shipboard microgrids, port facilities, islanded communities, desalination
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of infrastructure and technology systems for mathematical/computational modeling and control theory for life-cycle management optimization and policy of smart and sustainable infrastructure and environment systems