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Field
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Requirements a) Develop new R&D (research and development) topics in the field of high-energy hadron and nucleus collisions; b) Analyze data recorded by the ALICE detector at the LHC accelerator, CERN, using
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the consolidation and structuring of competitive research units in the SUG universities, in the public research organizations of Galicia and in other entities of the Galician R&D&i System by 2025, modality A
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, including time series analysis and statistics (e.g. mixed effects modelling) Capacity to develop computer code and experience with programming languages (Matlab, Python, R) and geospatial tools (e.g. ArcGIS
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of Decree-Law no. 60/2018 of 3 of August, and any formalities established therein must be fulfilled by the date of the act of contracting. Preferred conditions a)Programming skills, particularly in the R
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Helmholtz-Zentrum für Infektionsforschung GmbH | Braunschweig, Niedersachsen | Germany | 17 days ago
sample collections Conduct and supervision of laboratory analyses, in particular immunological assays Data management and programming in R and Python Writing and contribution to original publications
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, within the scope of the R&D project "PEERWISE: Peer Feedback Susceptibility in Adolescent Depression – Exploring Neurocognitive Mechanisms and Psychopharmacological Implications", PI Liliana Patrão Capitão
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) experience with collection and analysis of human physiology, EEG, eye-tracking and behavioural data in a cognitive neuroscience lab. Good to advanced programming skills (Matlab, Python, R) for experimental
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data analysis pipelines using ImageJ, R, MATLAB and relevant programming languages. Plan, troubleshoot and optimise experiments, maintain meticulous records, and prepare data, manuscripts and grant
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activities in the scientific area of Psychology, within the scope of the R&D project “Factors in the response to intervention in different types of reading disabilities”, ref. COMPETE2030-FEDER-00736600
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activities in the scientific area of Psychology, within the scope of the R&D project “Promoting Mental Health through Interpersonal Synchrony enhancement in Depression”, ref. COMPETE2030-FEDER-00769800