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equipped with variable‑speed electric machines. The objective of this evaluation is to determine whether the proposed model improves the prediction of additional losses introduced by the manufacturing
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control in one large foundation model. Using an input image of the robot’s surroundings and a textual command, these models are able to output low-level robot actions that can be executed to accomplish
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model improves the prediction of additional losses introduced by the manufacturing process. The successful candidate will contribute to research on generalizing some advanced magnetic material model
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cultural interpretation with language models. The position is part of the research project “CuRe: Cultural Reasoning for Responsible Language Model Development” (DFF project 5334-00088B), funded by
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from large loads, such as data centres. Evaluate strategies to prevent or damp harmful oscillations. Requirements: Master’s degree in electrical power engineering or a related field Fluent written and
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Future robots must perceive, predict, communicate, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering
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. Evaluate strategies to prevent or damp harmful oscillations. Requirements: Master’s degree in electrical power engineering or a related field Fluent written and verbal communication skills in English
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, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering-and-automation/mobile-robotics ) and Intelligent
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: Extending full-spectrum non-gray models for gases to solid particles Experimental characterization of fuel particles using FTIR Mathematical model formulation and programming Model implementation in
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candidates should have Master’s degree in computer science, mathematics, electrical engineering, or related fields; Fluent written and verbal communication skills in English; Ability to work both