Sort by
Refine Your Search
-
the preparation of technical reports on the algorithms, mechanisms, models, or protocols developed; - collaborate in the development of new communications solutions for extreme environments; - contribute to co
-
interfaces (HMI), and industrial-grade communication protocols for automation in electric power systems.; • Develop and adapt a test network — a simulation model or a replica of a real network — for DIgSILENT
-
learning models for generating artificial data using generative models. The result will be high-fidelity medical data. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - extend the knowledge
-
systems and DTs for fault and failure diagnosis, and simulation of future scenarios related to the impact of O&M strategies.; 3) Digital modeling of components and equipment, such as battery banks and
-
.; Minimum requirements: - Experience with different key-value store systems, including RocksDB, BlobDB, Parallax, WiscKey, and Keigo; - Solid knowledge of the key-value separation organization model; - Solid
-
the state of the art in the fields of smart buildings, digital twins, and the development of building energy optimisation algorithms; Use of methods and tools for energy systems modelling and optimization.; 3
-
INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
; - survey and analyze the state of the art in emerging wireless networks, including simulation aspects; - collaborate in the preparation of technical reports on the algorithms, mechanisms, models
-
; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - Identify state-of-the-art Vision-Language Models for image captioning; - Benchmark the models in occlusion scenarios; - Cooperate in writing
-
protocols for data collection with motion capture systems and curation of the resulting data - Design generative models for the creation of human movement datasets for training AI models - Evaluate
-
, energy consumption, and accuracy.; ; Training deep learning models, especially in LLMs, faces critical challenges that compromise the optimal use of GPUs. These bottlenecks result in poor computational