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This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
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industry needs while working on projects at SIT. Key Responsibilities Design and develop a prototype of an Artificial Intelligence (AI) model with deep learning algorithm to detect, distinguish and identify
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development of the LOTUSIM-Energy simulator and its associated autonomy components. Their main responsibilities will be: - Developing and integrating multi-physics simulation models for maritime, aerial, and
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, secure, scalable, and human-centered mission capabilities prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities identify and investigate
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reinforcement learning algorithms and contribute to the joint development of the broader modelling and policy framework. Your work will focus on multi-criteria reinforcement learning, uncertainty-aware decision
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(CI) to design, build, and optimize high impact computational tools, algorithms, and analytical workflows that power innovative research in medicine. You’ll manage and analyze large datasets and
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, which has the advantage of only modifying the software, for several years. A first maximum a posteriori type algorithm was recently developed during a thesis carried out in our laboratory. The final
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enhancements, including advanced navigation algorithms, swarm intelligence, cyber security hardening, and payload-specific control systems. Key Responsibilities: Control Augmentation Development: Design
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otherwise be lost in the glare of their host stars. The primary goal of this PhD is to develop a novel active algorithm capable of achieving real-time starlight suppression across all wavelengths. The PhD
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collaborate closely with Professor Colin Meyer at Dartmouth College to develop new models of polynya dynamics, efficient algorithms for inversion of surface signatures, and deeper understanding of controls