705 computer-programmer-"https:"-"FEMTO-ST"-"Inserm" "https:" "https:" "https:" "https:" "https:" "P" positions at University of Sheffield
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Crop Domestication, Diversification and Improvement School of Biosciences PhD Research Project Self Funded Prof C P Osborne Application Deadline: Applications accepted all year round Details Are you
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BBSRC Yorkshire Bioscience DLA Programme: Human Stem Cell-Based Approaches for Neurotoxicity Testing of Environmental Contaminants (CASE Project) School of Biosciences PhD Research Project
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"ROSEHIPS" Programme Grant. The ROSEHIPS project is focussed on creating new technology for Population-Based Structural Health Monitoring (PBSHM). It is a consortium between the Universities of Sheffield
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ACCE+ DLA Programme: Detecting rapid evolutionary responses to climate change in UK plants School of Biosciences PhD Research Project Competition Funded Students Worldwide Dr Luke Dunning, Prof C P
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ACCE+ DLA programme: Landscape-scale drivers and limits of endangered species spatial and temporal distribution School of Biosciences PhD Research Project Competition Funded Students Worldwide Prof
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BBSRC Yorkshire Bioscience DLA Programme: Genomics and development of an exaggerated sexual trait in stalk-eyed flies School of Biosciences PhD Research Project Competition Funded Students
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BBSRC Yorkshire Bioscience DLA Programme: From Flies to Fish: Exploring Neural Synchrony in Visual Processing School of Biosciences PhD Research Project Competition Funded Students Worldwide Prof M
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& Development Your training will begin with an intensive six-month programme at the University of Hull, drawing on the expertise and facilities of all four academic partners. It is supplemented by Continuing
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ACCE+ DLA Programme: Assessing the Future Effectiveness of Spatial Conservation Networks in tetrapods School of Biosciences PhD Research Project Competition Funded Students Worldwide Prof Gavin
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skill via an intrinsic reward. Science Advances, 10(13), eadj3824. https://www.science.org/doi/full/10.1126/sciadv.adj3824 Durstewitz, D., Koppe*, G., & Toutounji*, H. (2016). Computational models as