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Field
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record of scientific productivity is preferable. The successful applicant must have a Ph.D.in Computer Science, Data Science, Statistics, Mathematics, Physics, Engineering or related field at the start of
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of transmission electron microscopes and/or scanning electron microscopes Knowledge of artificial intelligence and machine learning and their applications in electron microscopy Knowledge of computer programming
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In the Phytophotonics department, you will work as part of an interdisciplinary team at the interface between plant sciences and optical technologies. The focus is on various spectroscopic and imaging
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contribute to the structural characterization of NS3–inhibitor complexes Process and analyze cryo-EM data using established computational pipelines and structural modeling tools Apply, or develop expertise in
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! Scientists have speculated about the inherent potential of molecular systems for information processing since the dawn of computer science. However, the digital computing paradigm is inherently ill-suited
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highly motivated Doctoral Research Fellow in a full time (100 %) fixed term position available for three (3) years at the Faculty of Computer Science, Engineering and Economics, Department
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the Phytophotonics department, you will work as part of an interdisciplinary team at the interface between plant sciences and optical technologies. The focus is on various spectroscopic and imaging methods
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teaching or other departmental duties, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at a Master’s level in Computer Science, Mathematics, or a closely related subject
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) in an appropriate discipline. Subject Area Computer Science & IT, Electrical & Electronic Keywords Artificial intelligence, floating-point arithmetic, numerical analysis, computer arithmetic, machine
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real-time during behavioural tasks Integrating virtual reality paradigms with behaviour and imaging to assess decision-making processes Exploring potential therapeutic interventions for NMDA receptor