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Field
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computer science or electrical engineering from a reputable university On top of systems and/or hardware security, we also consider applicants who have instead worked on computer systems or hardware design topics
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, optogenetic and electrical stimulation, neuromodulation and lesion-based validation, signal processing, computational network analysis, and dissemination of results. The postdoctoral associate will work with
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Robust Automatic Fact Checking (ExplainYourself)’, as well the Pioneer Centre for AI. Who are we looking for? Applicants should hold a PhD degree or equivalent in Computer Science or a related field, and
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works on the future of our power system. Job requirements We are looking for candidates who bring: A PhD in electrical engineering, power systems or a closely related field, obtained or close to
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frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems
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individuals holding a PhD in the Life Sciences or an M.S. degree with extensive experience are encouraged to apply. This position will be hired at either the Postdoctoral Research Associate classification
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Full time, fixed term for 2 years with the possibility of extension Join the School of Electrical and Computer Engineering and contribute to pioneering research redefining CubeSat technology Base
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dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning. The ideal candidate has
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opportunity The School of Electrical and Computer Engineering at the University of Sydney is seeking to appoint a Postdoctoral Research Associate to contribute to an exciting project focused on the challenge
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electrical stimulation. Assess mitochondrial function and cellular respiration through mitochondrial stress testing methodologies. Utilize techniques including qPCR, Western blotting, histology, proteomics