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: Salary negotiable and commensurate with experience. Required Qualifications: PhD in Medical Physics from a CAMPEP-accredited program Completion in a 2-year medical physics residency Certified
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environment who will supervise the PhD and collaborating with the rest of the Doctoral Network fellows. Where to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Electrical
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PhD position is available at the Department of Electrical Engineering , Faculty of Engineering Sciences and Technology with the research group Electromechanical Systems and the HYDROGENi project
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Nantes Université, École Centrale Nantes, CNRS, GeM, UMR 6183, Nantes F-44000, France | Nantes, Pays de la Loire | France | 6 days ago
/offre/2817 Funding category: Contrat doctoral environ 2300 euros brut mensuel PHD Country: France Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/137272 Requirements
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100
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INESC COIMBRA - INSTITUTO DE ENGENHARIA DE SISTEMAS E COMPUTADORES DE COIMBRA | Portugal | 1 day ago
support from FEDER and national funds through FCT, I.P., under the following conditions: Scientific Area: Energy Admission requirements: Holders of a PhD degree in Electrical and Computer Engineering, Civil
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14 Mar 2026 Job Information Organisation/Company Scuola IMT Alti Studi Lucca Research Field Computer science » Modelling tools Engineering » Control engineering Physics » Applied physics Engineering
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PhD degree in Electrical engineering or any related or advanced degree preferred. Specialty in power systems and distribution systems. Experience in commissioning energy storage systems and/or inverter
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Requirements Student enrolled in a PhD programme in Electrical and Computer Engineering Selection process Contest Evaluation Method(s) Curricular evaluation weighted to 50% on a scale of 20 points with a minimum
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further latency. Crucially, current MRI systems lack any form of predictive intelligence that could inform optimal configuration ahead of, or during scanning. The Computer Engineering (CE) section