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practice – 0 points. c)Specific knowledge (CE): knowledge of the preparation and optimization of mixtures of metal powders with polymeric materials; knowledge of additive manufacturing; knowledge
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professional/academic practice – 0 points. c) Specific knowledge (SK): Experience and knowledge in direct and indirect additive manufacturing systems. Experience with the FullControl library for gcode
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Scientific area of Cognitive Neuroscience and Psychology I.I - Grant Recipients: Students enrolled in a PhD program in the scientific field of Cognitive Neuroscience and Psychology. I.II - Ineligible
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Experience with Python and Pyomo; - Fluency in English (spoken and written); - Knowledge
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: IT137- 25 -31 I - Legal admission requirements Cognitive Neuroscience and Psychology I.I - Grant Recipients: Students enrolled in a PhD program in the scientific field of Cognitive Neuroscience and
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performance will be assessed according to the following weights and criteria: - Criterion 1 - Specific knowledge related to the work plan, especially in the areas of technology acceptance, economics and
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: Extensive knowledge of biomedical signal and image processing methods. Some knowledge of machine learning techniques and advanced statistics. Prior familiarity with the neuroengineering sector and its
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knowledge – 10% - Criterion 2: Specific knowledge related to the work plan – 25% - Criterion 3: Adequacy of the candidate’s profile to the work plan to be developed – 25% - Criterion 4: Knowledge of foreign
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(I) (60%) VII.I - AR - In the evaluation of the academic record, the candidates' academic performance will be assessed according to the following weights and criteria: - Criterion 1: Academic knowledge
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of one Research Fellowship within the scope of the R&D project “CATTLE IN MOTION: Knowledge, circulation and environments in the history of cattle in Portugal, 1750-1960” (2023.12421.PEX) funded by