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two companies. The project has partners from eight different EU countries. All 15 PhD projects are within the overall theme of neuromorphic computing and analog signal processing, targeting applications
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teach courses in the Master of Science in Biomedical Informatics (https://bmi.bsd.uchicago.edu ) program. These positions are renewable. Compensation is dependent on qualifications. These positions
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) Desirable Skills: • Prior experience in light-matter interaction, quantum information, quantum computing. • Proficiency in computer programming matlab, python, mathematica. How to Apply and required documents
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disciplines: Data Science, Artificial Intelligence and Cloud Systems and Security. Our PhD students and faculty conduct world leading research in many areas of Computing, including in: Artificial Intelligence
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degree (or equivalent) in geography, computational social sciences, computer sciences, climate sciences, environmental sciences, environmental engineering, water resources, digital humanities, or related
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software (Windows OS; MS Office, etc) and medical applications. Does this position have supervisory responsibilities? No Preferred Education/Experience AuD/PhD and eligibility to obtain KY audiology license
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. Experience in one or more scientific computing languages (Julia, Python, Matlab, etc) You must meet the requirements for admission to the faculty's Doctoral Programme (https://www.ntnu.edu/nv/phd) Good oral
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., Mendoza, M., Vetter, R., & Herrmann, H. J. (2016). Particle-Fluid-Structure Interaction for Debris Flow Impact on Flexible Barriers. Computer-Aided Civil and Infrastructure Engineering, 31(5), 323–333
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» Computer engineering Computer science Mathematics Engineering » Mechanical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 27 Mar 2026 - 17:00 (Europe
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision