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Field
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Machine Learning Researcher to join a multidisciplinary team of fabrication engineers and AI specialists at the University of Southampton, within the School of Electronics and Computer Science, working in
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PhD qualification degree in Electronic Engineering or Computer Science Familiarity with pinching antennas and machine learning Good written and oral communication skills Proficiency in python
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the advanced solutions to real-world applications such as cyber security compliance. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent
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the advanced solutions to real-world applications such as cyber security compliance. Job Requirements: Preferably PhD in computer engineering, Computer Science, Electronics Engineering or equivalent. Independent
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well as optical and laser setups Develop and implement protocols for quantum computing and quantum sensing experiments Collaborate closely with a multidisciplinary team of PhD Students, technicians, and engineers
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preferential viewing behavior, using large-scale electrophysiology, behavioral experiments, and computational modeling. We welcome applications from recent PhD graduates who are interested in these or related
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requirements Essential: PhD (or near completion) or equivalent qualifications and experience in Mechanical Engineering, Applied Mathematics, Physics, Acoustics, Computational Science or a closely related
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Engineering » Materials engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 5 May 2026 - 23:59 (Europe/Vilnius) Country Lithuania Type of Contract Permanent
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processing, mining, chemical or geological engineering, or a PhD in a related field with mining/mineral processing experience. Knowledge of process mineralogy, froth flotation through past research, coursework
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on methodology and academic writing Other career-promoting work Required selection criteria A doctoral degree (PhD) in solid mechanics, computational mechanics, or a closely related field, with a strong academic