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Field
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and Humanities of the University of Lisbon. 2. The scholarship will be awarded for 3 months, and may be renewed up to a maximum of 12 months and during the eligibility of the project. 3. The activities
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and field validation activities required for the characterization of the study area and the assessment of the resulting models. The expected outcomes are a functional modelling tool integrated with
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an empirical causal inference framework that combines cross-country panel econometrics with micro-level research evidence. Planned activities: (i) critical literature review; (ii) development of the structural
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degrees and diplomas documents, or their respective recognition when awarded by foreign higher education institutions are not mandatory in the application phase, being replaced by a declaration of honor of
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approaches to study target engagement, target validation, molecular recognition, drug action, and proteinligand interactions. Minimum Qualifications: Applicants must have a Ph.D. or equivalent doctoral degree
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research, and teaching across UCL Energy Institute , UCL Institute for Environmental Design and Engineering , UCL Institute for Sustainable Heritage , and UCL Institute for Sustainable Resources . About the
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presented to the competition. The academic degrees and diplomas documents, or their respective recognition when awarded by foreign higher education institutions are not mandatory in the application phase
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 2 months ago
for Higher Education: http://www.dges.gov.pt ). Notwithstanding this declaration, the contracting of the scholarship will only occur/be concluded upon presentation of proof of recognition of the academic
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are not presented to the competition. The academic degrees and diplomas documents, or their respective recognition when awarded by foreign higher education institutions are not mandatory in the application
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Environments Work plan: - The activities to be carried out will focus on the study and evaluation of automatic speech recognition technologies, with particular emphasis on deep learning-based approaches and