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Postdoctoral position_Quantitative Profile – funded by FIS2 – BADGE project Microbial-Driven Bile Acid Modifications and Their Impact on Gut Ecology Codice grant: FIS-2023-03089 CUP: E53C25000390001
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Preferred Qualifications : Competitive candidates should be highly motivated and possess a PhD in quantitative/spatial ecology of wildlife or a related discipline with a strong quantitative emphasis (ABD
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
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Postdoctoral positions_Experimental Profile – funded by FIS2 – BADGE project Microbial-Driven Bile Acid Modifications and Their Impact on Gut Ecology Codice grant: FIS-2023-03089 CUP
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
socioeconomically complex regions like the Amazon. This PhD will explore how tropical forests are functionally adapting to climatic pressures such as drought and warming, and how these ecological shifts intersect
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, such as R, Python, or Machine Learning, to identify patterns in biological factors, disease and mortality; co-supervising and mentoring PhD candidates, MSc and BSc students; collaborating with national and
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samples, laboratory cell lines and animal models. Ongoing and future projects include (i) genomic and functional characterization of molecular drivers of women’s cancers, (ii) biology and therapy
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modeling of mosquito-borne diseases as proven by peer reviewed publications. Demonstrably strong programming skills in R or Python. Experience with population biology, population genetics, or ecological and
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researcher interested in studying human-associated microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational biology
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postdoctoral researcher interested in studying human-associated microbial communities in health and disease. The ideal candidate has the following qualifications: A PhD degree in bioinformatics, computational