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modeling and simulation experience in PCB design experience in control system design using analog/digital sensors and DSPs/microcontrollers familiarity with HVAC systems and thermal/electrical co-design is a
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, specialized compilers, and robust algorithms and implementations, in addition to the creation of dedicated design tools and methodologies. The Computer Engineering (CE) section of the Department of Quantum
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optimization algorithms, you will design structures that deliberately harness modal couplings to exhibit tailored nonlinear behaviour, with direct applications in ultrasensitive resonant sensing. Together
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the second direction, you will explore the geometric design of nonlinear systems. Using nonlinear reduced order modelling (ROM) integrated with optimization algorithms, you will design structures
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stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic mechanisms are needed to be derived
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, prove the convergence and stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic
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requirements described will be excluded. Preferential factors: Experience in image analysis and processing using AI algorithms; English language proficiency; Portuguese language fluency. APPLICATION
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closely with a small, dedicated team, you will: Design and implement SLAM-based navigation algorithms for GPS-denied forest environments (45%) Develop multi-sensor integration software for LiDAR, cameras
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-identified scans, records and sensor feeds to answer questions such as: Can we predict a patient’s response to treatment without ever seeing their raw file? Can an algorithm learn the warning signs of trouble
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the ground, in different weather conditions. 4) develop methods for sensor management and data fusion linked with inference and decision making, jointly applied to several wildfire detection tasks. 5) embed