17 evolution "https:" "https:" "https:" "https:" "https:" "https:" "BioData" positions at Instituto Politécnico de Bragança
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their application through the platform at http://concursos.ipb.pt , along with an up-to-date curriculum vitae, a copy of the qualification certificate, a motivation letter and any other relevant evidence, such as
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and dated, delivered, together with all attachments, through the IPB electronic competition platform (http://concursos.ipb.pt ) and must contain the following elements: a) Full identification (full name
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21244, NORTE2030-FEDER-02214300”, funded by the “European Regional Development Fund (ERDF), Northern Regional Programme (Norte 2030) of Portugal 2030”, under the following conditions: 1. Scientific Area
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21244, NORTE2030-FEDER-02214300”, funded by the “European Regional Development Fund (ERDF), Northern Regional Programme (Norte 2030) of Portugal 2030”, under the following conditions: 1. Scientific Area
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: Statute of the Scientific Research Fellow, approved by Law No. 40/2004, of August 18, as amended; FCT, I.P. Research Grant Regulations in force (https://www.fct.pt/apoios/bolsas/docs
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Description A call for applications is open for a Research Grant within the scope of the project “Platform based on business models with applications for the development of local electricity markets and
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Development Fund (ERDF)”, under the following conditions: 1. Scientific Area: Agri-food Science and Technology, Biotechnology, Pharmacy and Health 2. Admission Requirements: 1) Student enrolled in an Agri-food
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the development of the following main tasks: i) Definition of an architecture for a digital representation with a digital twin of sensorized surfaces. ii) Integration of real-time data from Internet of Things
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Collection Instrument and statistical data processing; (3) Development and management of the database and respective statistical analysis; and (4) Preparation of scientific articles. 4. Objectives
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, in collaboration with researchers in the computational field; d) Contribution to the development, validation, and optimization of predictive models (Random Forest, Gradient Boosting, Neural Networks