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Field
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requirements, as well as the design of data models, synchronisation algorithms and analysis and learning models applied to brain and physiological signals. The objectives of this fellowship are: 1. To survey
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
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postdoctoral researcher with: A PhD (or near completion) in Computer Science, Computational Biology, Mathematics, Bioinformatics, or a related discipline. Proven expertise in machine learning and algorithm
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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, consecutive or interpolated, cannot benefit from the scholarship in competition; Candidates enrolled in a degree course: Enrollment in a PhD in the area of Informatics; Proof of academic qualifications
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Researcher (R1) Positions PhD Positions Country Portugal Application Deadline 15 Oct 2025 - 17:00 (Europe/Lisbon) Type of Contract Not Applicable Job Status Not Applicable Is the job funded through the EU