459 algorithm-"Multiple"-"Prof"-"U" "NTNU Norwegian University of Science and Technology" PhD positions
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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Computing (e.g., memristor modeling/simulation/manufacturing) and Edge AI related areas (e.g., AI algorithms, AI accelerator, VLSI). Background Investigation Statement: Prior to hiring, the final candidate(s
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experience in one or more of the following areas: machine learning, reinforcement learning, algorithmic trading, or data-driven modelling. Excellent communication skills: Solid written and verbal communication
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imaging phantom-based evaluation of quantitative SPECT/CT; reconstruction algorithm development; establishing a secondary standards laboratory for unsealed source metrology through gamma spectrometry
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You
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behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help of the simulation tool To support in the development and
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advantages for manipulation and locomotion, but current control algorithms do not fully exploit their capabilities. Most rely on approximations tailored for rigid systems or require extensive sensing and
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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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operate safely around humans. They offer unique advantages for manipulation and locomotion, but current control algorithms do not fully exploit their capabilities. Most rely on approximations tailored