410 coding-"https:" "https:" "https:" "https:" "Babes Bolyai University" positions in Netherlands
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drones and outdoor data collection with international teams, and have an interest in coding and handling large spatial and temporal datasets, this position is for you. This PhD offers the opportunity
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; • Conduct focus groups & dilemma-game workshops with lecturers, managers and support teams; • Transcribe, code and thematically analyse qualitative data (NVivo); • Co-create feasible, context-specific
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encouraged to visit the ESA website: http://www.esa.int Field(s) of activity/research for the traineeship You will contribute to a range of activities of the Technology Coordination and Planning Office, in
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Structures Inflatable and Deployable Structures Launchers / Re-Entry (Hot Structures) / Planetary Landing Vehicles Crew Habitation / EVA Suits You are encouraged to visit the ESA website: http://www.esa.int
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content, the execution of malicious code on connected devices, or the abuse of limited resources. The idea is to assess the resistance of these models against new attacks, using techniques coming from
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within brain networks. Among several proposed mechanistic accounts, the Bayesian predictive coding framework has gained increasing prominence. According to this framework, perception of proprioceptive
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data and code. The focus will be on making frictions and controversies characteristic of different ‘rurban’ spaces and practices publicly debatable in experiential ways to support collective imagination
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perform among the top-10% of test-takers on the quantitative part of the GRE; applicants with a Q score below 160 will not be considered. Advanced quantitative skills, including experience with (coding in
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well as the underlying architecture and code. -------------------------- Why trading? If you want to get near-immediate feedback on your best ideas, while leveraging cutting-edge technology, the trading industry is hard
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are encouraged to visit the ESA website: http://www.esa.int Field(s) of activity for the internship You can choose between the following topics: 1) Topic 1: Machine Learning for recognition of planetary materials