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hardware realization of neuromorphic systems, bridging neuroscience and electronics. The project combines expertise in circuit design, machine learning, and neurotechnology, and aims to deliver innovative
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postdoctoral researcher with a PhD in Energy Engineering, Mechanical Engineering, Chemical Engineering, Environmental Engineering, or a related field, and strong expertise in techno-economic assessment of Power
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international levels. For more information about SDU LCE, please visit www.sdu.dk/lifecycle. Profile and Responsibilities We are seeking a highly motivated postdoctoral researcher with a PhD in Energy Engineering
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refinement. Publish results in peer-reviewed journals and present findings at international conferences Required Qualifications PhD in proteomics, analytical chemistry, physical chemistry, or a closely related
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is expected to hold a PhD degree relevant to the topics of the fellowship. Such a degree might be in (Medical) Sociology, Public Health, Epidemiology, or another area related to survey data analysis
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
workshops. Qualifications Applicants must hold a PhD degree (or equivalent) in a relevant field. Suitable disciplinary backgrounds include but are not limited to: Computer Science, Data Science, Artificial
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should hold a PhD in Electrical or Electronic Engineering (completed within the last 5 years) with strong experience in CMOS IC design. The ideal candidate has: Strong background in analog and/or mixed
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). Applicants should have completed their PhD in Finance or a related area prior to starting. We also encourage seasoned candidates with a strong research pipeline and teaching experience to apply. Job
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, materials science, and artificial intelligence. What we expect Applicants should hold a PhD in electronic engineering (the degree should have been completed within the last 5 years at most): Strong background
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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive