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research group investigates the effects of different models of hypoxia (real and/or simulated) on central and peripheral physiological adaptations in both humans and rodents. The successful candidate is
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(HR+/HER2-) and aims to develop predictive models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue
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purpose including a proposal for development based on the project (available at: News – https://www.cosmopoliticasdocuidado.net/ ), and a Curricular Summary using the model established by FAPESP (the São
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qualitative and quantitative aspects. - Contribute to high-impact academic publications, disseminating theoretical and methodological innovations generated by research. - Establish a replicable model for
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position within a Research Infrastructure? No Offer Description The research proposal aims to use machine learning, including large-scale language models, to analyze large datasets of smaller Solar System
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targets through the investigation of anti-inflammatory peptides derived from animal venoms. The activities involve exploring the biology of the peptides and their in vitro effects on cellular models
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performance in the PhD course; articles in international journals on the subject of the fellowship project; experience in modeling, numerical simulations, and computational programs of chaotic particle
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summary, up to four pages, following this model https://fapesp.br/en/6351 ; 2. List of up to 5 of your main publications, with a brief description of the main results of each of these publications (maximum
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to anthropogenic climate change. Nevertheless, these extreme events may be modulated by large-scale climate variability modes across a wide range of spatial and temporal scales. Using large ensemble multi-model
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from animal venoms. The activities involve exploring the biology of the peptides and their in vitro effects on cellular models of inflammation and nociception. Candidates must have obtained