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to the job description and requirements above) CV and other proof of scientific activity (publications, conference papers etc.) A copy of the master´s degree certificate and an official transcript of records
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LevelMaster Degree or equivalent Research FieldChemistryEducation LevelMaster Degree or equivalent Skills/Qualifications The applicants should fulfil the following requirements: Master´s degree in the field
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FieldTechnologyEducation LevelMaster Degree or equivalent Research FieldChemistryEducation LevelMaster Degree or equivalent Skills/Qualifications Applicants should fulfil the following requirements: Master´s degree in
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supervision. Requirements include a Master's degree, proficiency in programming, and demonstrated interest in the research topic. Description Fine motor tests, particularly drawing (e.g., spiral drawing test
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journals, supporting teaching activities, and co-supervising students. Requirements include a Master's degree in relevant fields, proficiency in programming, strong analytical skills, and a demonstrated
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requirements: master's degree in power electronics; B2 English level certificate if English is not the native language and the language of instruction in MSc study was not English; practical experience in
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should fulfill the following requirements: master's degree in power electronics; B2 English level certificate if English is not the native language and the language of instruction in MSc study was not
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fulfill the following requirements: master's degree in smart grids or related areas with cyber-components; B2 English level certificate if English is not the native language and the language of instruction
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needed as per the rules at TalTech (such as: proof of English language proficiency which must be at least B2, Scans of original qualification documents, etc; see also).Applicants may be contacted
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, analysis, and mapping for data collected in extreme environments. The main aim of this project is to develop state-of-the-art data analysis and mapping methods that are efficient, reliable, and near real