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- Bucharest Universty of Economic Studies
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Postdoctoral Researcher position. Part-time 80 hours/month distributed unequally, gross hourly salary of 60 lei, fixed period until June 30, 2026. The project is entitled “A Study of Consumer Trust in Online
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Postdoctoral Researcher position. Part-time 32 hours/month distributed unequally, gross hourly salary of 80 lei, fixed until June 30, 2026. The project is entitled “A Study of Consumer Trust in Online Reviews
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Postdoctoral Researcher position. Part-time 80 hours/month distributed unequally, gross hourly salary of 80 lei, fixed period until June 30, 2026. The project is entitled “A Study of Consumer Trust in Online
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concepts in information processing using machine learning algorithms LanguagesROMANIANLevelExcellent Research FieldComputer scienceYears of Research ExperienceNone Additional Information Selection process
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Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Development and implementation of algorithms and software solutions: Designing
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project MAREHC – “Maximizing the Renewable Energy Hosting Capacity of Distribution Networks”. Project Background The PNRR MAREHC project aims to strengthen the innovation capacity of the Romanian RDI system
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research and innovation lab offers metadata, algorithms, and code snippets to bridge the gap between practice and insightful modeling. IDA develops valuable metrics which translate into investment
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development Signal processing and control algorithm implementation Communication protocol design and optimization Cross-disciplinary teamwork Specific Requirements Collaboration with multidisciplinary teams
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distribution under a suitable time scaling. The purpose is to offer a deeper analysis of this class of stochastic processes concerning their stochastic and statistical analysis and to propose some non-Gaussian
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Hermite processes. Self-similar processes are stochastic processes that are invariant in distribution under a suitable time scaling. The purpose is to offer a deeper analysis of this class of stochastic