Sort by
Refine Your Search
-
Program
-
Field
-
INESC TEC is accepting applications to award 4 Scientific Research Grant - NEXUS - CTM (AE2025-0564)
the motivation letter, the specific Research Topic they are applying to.; ; The Work Programmes of each Research Topic are listed below:; ; Research Topic #1 – Data-rate Adaptation for Emerging Wireless Networks
-
Requirements. The applicants must reference, in the motivation letter, the specific Research Topic they are applying to.; ; The Work Programmes of each Research Topic are listed below:; ; Research Topic #1
-
benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
-
process and the results obtained. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: - To contribute to the specification and development of algorithms for optimizing energy systems with
-
visualisation (libraries such as Three.js, OpenGL, VTK, or similar); - Advanced knowledge of optimisation algorithms; - Previous experience with software development for logistics problems; - In-depth experience
-
algorithms to combine information on cardiovascular activity obtained from heart sound signals, electrocardiogram, and photoplethysmography. Investigate the inclusion of prior knowledge about the application
-
distributed systems. Minimum requirements: - Solid knowledge of database engine implementation; - Solid knowledge of optimization algorithms (Volcano/Cascades); - Practical development experience with
-
manipulators capable of adjusting their trajectory and resistance in real time in response to variable external loads. This module should integrate learning algorithms based on artificial intelligence, allowing
-
algorithms; Minimum requirements: - experience with cross-platform mobile development frameworks (Ionic); - experience in software development using the Python programming language. 5. EVALUATION
-
-oriented interfaces is desired.; In parallel, we intend to explore new optimizations, such as data deduplication, support for multi tenancy, and new scheduling algorithms. These optimizations should be