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Field
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electric machines•Nanomaterials for next-generation electronic and photonic nanodevices•Oxide materials for MEMS piezoelectric and multiferroic sensors/actuators•Solid-state devices such as solar cells
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/Qualifications Experience in: - Development of artificial intelligent algorithms. - Explanaible artificial intelligence - LLM experience - Virtual intelligence entities using reinforced learning
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of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping the technologies that underpin a more sustainable and
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participants of the Netherlands Twin Register, integrating genetic and psychological data where relevant. Beyond algorithm development, you will also address methodological challenges such as data quality, bias
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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are rapidly evolving – ranging from remote sensing and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured
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the following research areas providing a template for relevant directions: - Field Robotics with a focus on Arctic Environments - Autonomous Navigation and Motion Planning in Sensor-Degraded Disaster Environments
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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title: UDC-Inditex Chair of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01
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title: UDC-Inditex Chair of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy efficient Grant/funding period: START: 01