Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
scheduling algorithms to ensure operation continuity and reliable information exchange among batteryless sensors. Where to apply Website https://lavoraconnoi.unitn.it/research-assignments/dipartimento-disi
-
scanning and Time-of-Flight (ToF) sensors, to enable robust material identification directly in non-laboratory, real-world environments. The acquired data will be processed using advanced machine learning
-
detection, communication, cable management, electronic locks, Wi-Fi locks, network switches, point sensors, signaling devices and associated hardware. Responds to situations where systems have failed and
-
and communication delays. Besides, works considering both integrity attacks on sensors and actuators as well as on the network availability (denial-of-service) are rare. Furthermore, current approaches
-
externally funded, convergence research at the intersection of polymer chemistry, surface science, sensor technologies, environmental engineering, with Omics-driven approaches for materials discovery. This is
-
particularly relevant for large-scale systems (e.g., energy distribution networks, sensor networks, gene regulation networks, etc.). A first strategy to tackle this problem is to consider the global system and
-
opportunity The Carbon Analyst will be a member of Australian Antarctic Program Partnership (AAPP)’s project 5: Biogeochemistry, and will support at-sea biogeochemical sensor calibration, sample analysis, data
-
flow. A recent explosion in the number of sensor capable of measuring ice flow from space, and the maturation of projects targeted at extracting comprehensive records of ice flow (e.g. NASA’s ITS_LIVE
-
member in the Faculty of Science and Technology, in the following disciplines: IoT infrastructure and devices (sensors, embedded systems, etc.) Sensing technologies IoT security and privacy-enhancing
-
mechanics) with data-driven techniques. • Proficiency in Python (NumPy, TensorFlow/PyTorch) and MATLAB. • Familiarity with deep learning architectures, particularly recurrent neural networks (e.g., LSTM) and