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other sources to build knowledge graph.Researcher profile: Doctoral candidate.Research field: Applied Physics, Computer Science, Data Analysis, Machine Learning, Artificial Intelligence.Type of contract
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candidate.Research field: Applied Physics, Computer Science, Data Analysis, Machine Learning, Artificial Intelligence.Type of contract: Temporary.Job status: Full-time.Duration: 36 months.Application deadline: 15/05
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project (https://www.ipcei-batteries.eu ) aiming at the development of next-generation battery technologies. The activities of the successful candidate will focus on: development and validation of physics
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includes the evaluation of the efficacy of novel pharmacological approaches, psychotherapy techniques, targeted physical activity, and transcranial magnetic stimulation (TMS). This evaluation will based
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the preparation of the project's proposal. Job Requirements The ideal candidate should have: MSc in Energy engineering or similar. Know-how in code development applied to physics problems (H2 system and components
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experience in computational physics, with special emphasis on complex states of flowing matter and lately quantum computing for fluids as well. The research focuses on computational modeling of complex fluid
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to physics problems (H2 system and components). Good modelling practices, attention to detail and commitment to verification/validation. Proven experience in the modelling of Hydrogen technologies focuses
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Such yearly maximum amount corresponds to the gross amount 48.391,98€, including charges to be borne by the institution. Eligibility criteria Research titles, PUBLICATIONS AND RESEARCH PROJECT Selection process
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in code development applied to physics problems (H2 system, components and scenarios). Familiarity with engineering boundaries and competence on their definiitions. Good modelling practices, attention