638 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Uk
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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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strategic dissemination, ultimately aiming for widespread adoption and commercial success. If you are still awaiting your PhD to be awarded you will be appointed at Grade 6, spine point 30. Upon written
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. Concurrently, you will develop lower order analytical models and perform high fidelity computational simulations to corroborate experimental findings and propose other configurations to be subsequently
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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
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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work closely with Prof. Hanna Kienzler, Prof. Stephani Hatch, and Dr Rebecca Rhead as part of the Centre’s ‘Marginalised Communities’ programme. This involves partnering with Black and racially
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-responsive molecular machines. The project is funded by the European Research Council. Find out more about the Langton research group at: here About you Applicants must hold a PhD in Chemistry or a related
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to understand immune microenvironmental interactions; Integration and interpretation of complex datasets in collaboration with computational scientists You will be expected to take a lead in experimental design
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molecular and computational approaches. They will hold a PhD in a relevant subject, have a solid computational background, and be able to curate, analyse and interpret complex single-cell data sets