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neuroscience, and brain-computer interfaces, machine learning and deep learning, statistical modelling, regression methods, and uncertainty quantification, calibration, interlaboratory comparisons, and
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resonance imaging data among other imaging modalities, machine learning methods for prediction, treatment effect estimation, and contribute to understanding brain biomarkers of Alzheimer’s disease and their
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recent years in conjunction with Variational Monte Carlo methods and efficient optimization techniques to obtain excellent representations of the ground state of many-body quantum systems
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quantum complexity” - The project aims to study paradigmatic many-body topological phenomena (in particular, lattice gauge theories and fractional Hall effects) using concepts related to classical and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 5 days ago
repeated over several trials (to collect multiple samples) before making a decision. For these applications, statistical methods for hypothesis testing and estimation are needed, with formal guarantees
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Website https://fenix.tecnico.ulisboa.pt/fenixedu-admissions Requirements Research FieldEngineering » Computer engineeringEducation LevelUndergraduate Skills/Qualifications Admission Requirements 1
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policy. Students will gain an understanding of when and how to use various methods of program evaluation and will be exposed to both theoretical concepts and case studies. Estimated course enrolment: 100
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21 Apr 2026 Job Information Organisation/Company Instituto Superior de Engenharia do Porto Department Human Resources Department Research Field Engineering » Computer engineering Researcher Profile
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of Science, University of Southern Denmark (SDU), Odense. We seek a candidate with strong, documented expertise in computational drug design / computer-aided drug discovery. Preferred competencies include
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 8 days ago
supramolecular networks/IST-ID), (1801P.01682) 2024.14207.PEX, financed by national funds through FCT/MCTES (PIDDAC Workplan: This project focuses on self-replication driven by self-assembly, using computer