Sort by
Refine Your Search
-
Program
-
Field
-
holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Study the main exact subgraph counting algorithms identified in the survey (e.g., ESU/FANMOD, Kavosh, GTrie, FaSE, ORCA
-
. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Develop optimization algorithms for predictive energy management • Model consumption, renewable generation, storage and CO₂ emissions • Test the
-
. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: • Develop real-time optimization algorithms • Model multi-vector energy-water-hydrogen systems • Support the development of digital twins • Test the
-
of the proposed solutions. Activities will include the implementation and evaluation of algorithms for signal processing, detection, correlation, localization, and tracking of acoustic sources, as
-
analysis of data from wearable and clinical monitoring devices and clinical databases. Experimental evaluation of algorithms, development, and deployment. Support in data collection and documentation
-
wearable and clinical monitoring devices and clinical databases. Experimental evaluation of algorithms, development, and deployment. Support in data collection and documentation of the work performed. 4
-
of developed algorithms and their deployment. Support in data collection and documentation of the work performed. 4. REQUIRED PROFILE: Admission requirements: Master's degree in Biomedical Engineering
-
: • Develop real-time optimization algorithms; • Model multi-vector energy-water-hydrogen systems; • Support the development of digital twins; • Test the algorithms using operational data; • Prepare a technical
-
the resilience, safety, and security of critical infrastructures as core requirements. Moreover, it will boost the development and validation of novel AI algorithms, by the European AI community, through open
-
/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Study and improvement of developed algorithms - Automation of the model