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Field
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decoherence dynamics and other effects of quantum-classical correlations in complex fluid solvents. The methodology will be largely based on Lie group methods and structure-preserving algorithms in geometric
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progress in machine learning and artificial intelligence, the successful candidate will have primary responsibility to develop, implement, and test multimodal machine learning algorithms to analyze and
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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of algorithms for natural language understanding, structured command generation, and domain-specific model adaptation or fine-tuning. Integrate NLP and speech technologies (ASR/TTS) into a unified tactical signal
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research profile and prepare for the next career stage. Job Requirements: A PhD degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, Applied Maths, Physics, or any related
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. This role will contribute the development of novel machine learning algorithms for wireless sensing and communication and the proof of concepts for next-generation wireless communication, collaborating with
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Researcher (R1) Positions PhD Positions Country Portugal Application Deadline 2 Dec 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
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Job Reference: 1168098 About the Role: You will play a key role in advancing distributed and adaptive AI methods, focusing on scalable software frameworks, learning algorithms, and orchestration
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-forming converters and control algorithms for next-generation renewable and energy storage systems. The role will focus on control design, simulation, and experimental validation to support system stability