Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
this competition for at least 5 years after the PhD, with a relevant curriculum in the scientific area to which they are applying; b) Competences in geographic information systems, multi-criteria analysis models
-
two years followed or interpolated, in this type of scholarship; Requirements: Clear demonstration of skills in modeling and simulation of solids, fluids, and their interaction; clear demonstration
-
of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE-C05-i08 of the Recovery
-
from academic degree recognition processes. Preferential factors: a. Knowledge of developing artificial intelligence/machine learning (AI/ML) models and classifiers suited for embedded systems
-
AMALIA - Creation of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE
-
AMALIA - Creation of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE
-
nationals, stateless persons, and citizens with political refugee status are eligible to apply for this competition. Candidate eligibility requirements: Proven experience in simulation and modeling using
-
AMALIA - Creation of the Large-Scale Language Model of the Portuguese Language of Portugal (Automatic Multimodal Language Assistant with Artificial Intelligence), reference AMALIA, inserted in measure RE
-
sub-area of Biotechnology Applied to Health, within the scope of the project “CAN-TARGET – Decoding the Complexity of Cancer: Integrative Strategies to Model In vitro and Target the Multi-Cellular Tumor
-
Large Language Models (LLMs). Knowledge is valued both in advanced prompt engineering techniques (e.g., few-shot learning, chain-of-thought prompting) and in fine-tuning and adaptation of models (e.g