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of the project “PROSPER: Predictive models for sustainable protein recovery”, funded by FEDER and by National Funds through FCT (Operation No. 15391 — COMPETE2030-FEDER-00907300), under the following conditions
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tools. Processing of collected data; Implementation of Machine Learning; Development/implementation of the model prototype in the digital solution (app/platform) to support the clinical trial
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certificates shall be valid only if they are dully endorsed by an issuing entity, or if a recognition/equivalence document is produced stating that the foreign qualifications correspond to the same Portuguese
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models, and the discovery of novel pathways involved in both normal development and disease, driving progress in regenerative medicine and personalized healthcare. Where to apply E-mail positions@gimm.pt
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Engineering, specializing in Hydraulics; Degree completed less than 3 years ago; Knowledge in modelling urban water supply networks; Programming knowledge in Python and R; Knowledge in relational database
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or related fields. Experience in research or relevant activities in the project area, such as data analysis, statistical modelling, or software development. Good knowledge of statistical programming
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tools and their integration into the matRad treatment planning system; 3) development of tools that automatically identify for each patient the dose-response models that characterize the worst-case
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Life and Health Sciences Research Institute (ICVS), from the School of Medicine (EM) of the University of Minho | Portugal | 3 months ago
submission” of this Call, the candidates must submit in the application process a Declaration of Honor regarding the benefited Research Fellowships, issued as defined in the model attached to the present
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advancing the technology to a higher TRL level (from 2 to 5). The activities to be carried out under this scholarship correspond to WP2, Task 2.5, which involves experimental testing aimed at optimizing
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his/her scientific training. In particular, it is intended to develop and apply remote sensing methodologies and tools for the detection and modelling of habitats, as well as the extraction