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- University of Trás-os-Montes and Alto Douro
- Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa.
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of the project “HUMYK - Autonomous Community Composter", with operation code CENTRO2030-FEDER-01180100 (Nº 17322), co-financed by Centro 2030 Regional Program, Portugal 2030 and the European Union. The purpose
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within the scope of the operation A-MoVeR - Mobilizing Agenda for the Development of Intelligent Green Mobility Products and Systems, namely: 1) Development of prototype production methodologies; 2
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Environment; 4) Prototyping; 5) Testing and Evaluation; 6) Prototype Integration and Validation; 7) Publication of Results and Dissemination of Generated Knowledge. Applicable legislation and regulations: Law
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Characterization of Materials; 3) Hypothesis Formulation and Development in a Laboratory Environment; 4) Prototyping; 5) Testing and Evaluation; 6) Prototype Integration and Validation; 7) Publication of Results and
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f actual, reliable, and safe responses by LLMs and LVLMs (multimodal). • Integration of the developed contributions in the project prototype. • Coordination of activities with the other project
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screening technologies. The approach includes optimizing LDL uptake in lymphocytes, conducting high-throughput screening of bioactive compound libraries using AI-driven image analysis, and validating top
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for Grant Assignment and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all in their current wording, and by other applicable national and community legislation. Procedure
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aims to produce a prototype product of mycorrhizal fungi for use in olive groves as well as to produce micropropagated and mycorrhized olive seedlings. 5. Applicable legislation and regulations: Statute
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; Microscopy image processing and data analysis. 4.2. When the academic degree or diploma is awarded during the term of the studentship contracts, the studentship may continue as long as the activities provided
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images. If necessary, an interview will be held. In this case, the classification will be based on the weights of 75% (scientific and technological skills, experience) and 25% (interview). The selection