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developing simulation flows, analysis methodologies, and predictive models that enable Design-Technology and System-Technology Co-Optimization (DTCO/STCO) studies for future systems. You will work closely with
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Neuroimmunology Research Group/Cemcat is seeking to recruit a talented candidate to join our team and undertake a PhD. More information about our group can be found at: https://vhir.vallhebron.com/ca/recerca
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the Earth formed over a period of more than 30My), the solar-type neon in the Earth's mantle is an argument for the existence of such a captured atmosphere, which partially dissolved into a magma ocean. A
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supervisor), Professor Ingunn Studsrød (co-supervisor), and Associate Professor Marina Snipsøyr Sletten (co-supervisor). Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/302556/phd
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organisms and determine the environmental factors controlling their activity under future conditions. Ultimately, the project will improve our understanding of anaerobic microbial food webs in Antarctic
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function approximation and optimal control. ● Contribute to writing scientific papers on the project results and assist in disseminating these results at conferences and workshops. The selected candidate may
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ARDITI - Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação | Portugal | 2 months ago
Law no. 7/2009 of February 12, in its current version. 3. Jury Composition • President: Caroline Ferreira (OOM) • Effective Member: Carlos Lucas (OOM) • Effective Member: Filipe Alves (MARE-Madeira
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: The position is limited to 32 months. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz – WissZeitVG). Supervisory team: Supervisor: Prof. Dr. Martin
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experience in one or more of the following areas: Program evaluation Impact evaluation or randomized controlled trials Labor economics or workforce development programs Analysis of government administrative
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, physics of fluids, flow control... The main objective is to develop numerical tools to efficiently predict and to deeply understand flows in more and more physically and geometrically complex configurations