623 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Uk
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institutions in the programme grant and with supporting industrial partners. About you You should possess a university PhD degree in mechanical engineering or a similar discipline, preferably with experience
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no.: 4331 Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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the problem of induction”. How biological and artificial agents can use limited evidence to effectively learn and generalise is a long standing issue for psychology, AI/computational sciences, neuroscience and
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design, delivery, and evaluation of a multi-school research study investigating the impact of mathematical storytelling on secondary students’ mathematics learning and related outcomes. Working closely
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weighting The Department of Computer Science seeks to employ a postdoctoral researcher to work on a new project in the area of LLMs/multi-agent systems, under the direction of PI Professor Michael Wooldridge
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dynamics and (at intermediate redshifts) strong gravitational lensing, thus preserving and extending the team’s lead in this field. Applicants should have a PhD (or close to completion) in (Astro) physics
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of career. Experience in using qualitative data analysis computer software such as NVivo would be an advantage. Skills 13. Demonstrable ability to plan and manage research, both independently and as part of a
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, “Determining extinction correlates on geological timescales”. Providing guidance to less experienced members of the research group, including research assistants, technicians, and PhD and project students
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Among the many reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high