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: Project Scientist Salary range: The UC academic salary scales set the minimum pay determined by rank and step at appointment. See the following table for the current salary scale for this position: https
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Engineering » Electrical engineering Engineering » Electronic engineering Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Apr 2026 - 13:06 (Europe
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such as achievable rates, coverage, and energy efficiency, as well as optimize relevant system parameters. Applicants must hold a PhD degree or terminal degree from a recognized institution of higher
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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking to hire a research fellow (postdoc) to undertake a project to develop efficient AI and Machine
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Differential Imaging (CDI) to exploit the fundamental property of light coherence. The PhD will focus on two complementary approaches: 1) Enhancing CDI with machine learning: improve this technique using
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 11 hours ago
://drive.google.com/file/d/17SY2HfckkPZp8GVtRelkIxrGhikP92nN/view?usp=sharing Job Requirements REQUIRED: PhD in materials science, physics, electrical engineering, chemical engineering, or a related field by the start
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INESC COIMBRA - INSTITUTO DE ENGENHARIA DE SISTEMAS E COMPUTADORES DE COIMBRA | Portugal | 2 days 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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Basse Normandie. PHD title: Doctorat de Physique PHD Country: France Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/137565 Requirements Specific Requirements Applicant
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to adjust across different tasks and domains. Preferred Qualifications Doctor of Philosophy (PhD) in scientific or engineering field, preferably in computer science, electrical engineering or ICT. Experience
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between