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Ph.D degree in electrical engineering, computer engineering, computer science, or a related discipline Demonstrated experience developing, training, and applying AI algorithms to physical sensor data
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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Allowance** EUR 4736 EUR 710 EUR 660 Context: Agriculture and agronomy generate a wide variety of data (connected equipment, weather, environmental sensors
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technologies such as IoT, big data, analytics, computer vision, cloud computing, and artificial intelligence (AI). IoT devices help in data collection. Sensors plugged in tractors and trucks as well as in fields
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-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms to automatically identify, flag, and mitigate data artifacts
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6 Feb 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Programming Mathematics » Algorithms Mathematics » Discrete mathematics
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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available in Digital Endocrinology in the Marie Skłodowska-Curie Doctoral Network (ENDOTRAIN). Join Europe’s first doctoral network in digital endocrinology – integrating AI, sensor technology, omics, and
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some of the following skills: Localization and sensor fusion: Solid understanding of localization techniques and sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based