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Informatics and edge intelligence etc. Must have documented significant Knowledge/Research Background, or Must be able to demonstrate skills on Data Analytics and Machine Learning, in particular on distributed
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, machine learning, programming, software engineering, instrumentation, benchmarking, reproducibility and technological prototyping. The mandatory requirement for technical-scientific proficiency in English
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Engineering is one of the largest and most prestigious computing schools in Australia. It offers undergraduate programs in Software Engineering, Computer Engineering, Computer Science, Cyber Security and
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are built on a foundation of continuous learning and growth . We actively support professional development by providing all full-time staff employees with at least 80 hours of paid time per year and provide
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, for event reconstruction and classification, including potentially machine learning/AI Interpretation in suitable theoretical models Contribution to software activities that are required for wider use by DESY
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Documented ability to work in Python Experience with machine-learning methods for record linkage and text analysis Documented experience with machine-learning methods for image-to-text transcription
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funding for scientific research English proficiency for the purpose of conducting classes (and/or consultations) in this language fluency in Polish language strong computer literacy and readiness to learn
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an enthusiastic and highly motivated researcher. You have, or will shortly, acquire a PhD degree in the field of Human-Computer Interaction, Interaction Design or Interaction Technology or equivalent Ideally, you
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funding for scientific research English proficiency for the purpose of conducting classes (and/or consultations) in this language fluency in Polish language strong computer literacy and readiness to learn
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the group's core research areas, and a proven ability to conduct independent, high-impact research. Experience in cybersecurity for cyber-physical systems, digital twins, BIM, AI and machine learning