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than 14/20 (1 point); B. Knowledge of Interactive Systems Design, Cyber-Physical Systems, Predictive Maintenance Systems, Automation, Machine Learning and Artificial Intelligence, Sensor Networks
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to teaching and sharing their knowledge/approach with the next generation of young scientists by supporting the SNXG scholarship program at Swinburne University of Technology. There are three scholarships in
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. Specific Requirements Preferred requirements: Programming skills, namely in the domain of the R language; Good knowledge in the application of statistical methods applied to analytical epidemiology: survival
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demonstrate experience and skills in: a) Knowledge of and experience in the use of qualitative and/or quantitative research methodologies, demonstrable, for example, through co-authorship of publications
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regulatory networks in pathogenic yeasts, with impact on their pathogenesis, in order to strengthen knowledge regarding less well-studied yeast species. From the bioinformatics standpoint, the work will focus
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the scientific area of Chemical Engineering, enrolled in a doctoral degree. OR Master’s degree holders, in the scientific area of Chemical Engineering, enrolled in a non-degree-granting course. Knowledge of
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methods: a) motivation letter (20%), b) curriculum vitae (40%), and c) experience in the area of research/previous knowledge of concepts and technologies relevant to the execution of the project (40
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 19 days ago
organic synthesis chemistry and peptide chemistry # Knowledge in structural analysis (NMR, UV, HPLC, ITC) # Willingness to work with radioactive substances # Practical experience in the field of (radio
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– e.g. Food Science, Industrial Design, Project Management • Relevant experience in the food industry, ideally knowledge of new product development, process improvement and product launch protocols
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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 22 days ago
methods will be phased, as described below. 3. The evaluation of the "scientific and curricular background" will focus on the relevance, quality, timeliness, specific knowledge, and proven prior