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and AI techniques will be used to predict periods of harmful phytoplankton occurrence and to investigate their environmental triggers in the Galician Rías Baixas (NW Iberia). The work will also involve
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measurable. This can be approached through empirical analysis of large-scale simulations, through new (semi-analytical) models that predict the impact of introducing these vehicle types, or a combination of
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control of predictable and reliable biotechnologies”, a collaboration between the universities of Oxford, Bristol, and Imperial College as well as several industry and academic partners. The research
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University and participate in the doctoral training programme of the Doctoral School of Sciences. The position Only a fraction of the genome codes for the proteins in standard reference catalogs. Many small
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genetics/genomics. More about the position The project aims to develop novel computational methods and tools for predicting functional non-coding mutations in the cancer genome. These methods will integrate
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computational methods and tools for predicting functional non-coding mutations in the cancer genome. These methods will integrate diverse sources of information, including the biophysical principles of protein
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Additional Information Eligibility criteria Supportive and collaborative professional environment Stable and predictable working environment Employee benefits available at the University of Pécs Work Location
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collaborative professional environment Stable and predictable working environment Employee benefits available at the University of Pécs Work Location(s) Number of offers available1Company/InstituteUniversity
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in the position and briefly outline skills and experiences that directly relate to this position. Additionally, examples of code, reports, or other work product may be requested. Who We
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Organization U.S. Department of the Interior (DOI) Reference Code DOI-USGS-2026-70 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete