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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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on Compact Manifolds with Novel Feedback Coupling and Complex Network Optimization." Specifically, the selected candidate will address Research Objective (RO) (2) Investigate the dynamical phenomena of orbital
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conducting qualitative network analyses of the connections between land use, water quantity and quality, marine food webs and species, governance, and ecological, social and economic system dynamics and
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research in digital and high-frequency electronics, embedded systems, control, and communication, utilizing cutting-edge reconfigurable computing and sensors. The aim is to develop next-generation
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multisource data (IoT, sensors, satellite images, social media, administrative data). Understanding of urban planning issues (urban forms, basic services, sustainability, resilience). Personal and
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family of printable high-gauge factor wireless sensors by building and extending our related background intellectual property. Responsibilities : Collaborate with the development of a new family of RFID
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study qubit systems. A particular emphasis is on exploiting the manipulation capabilities of scanning probe microscopes to fabricate molecular quantum sensors on probe tips to detect the tiny electric and
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experimentation, isotopic measurements and modeling aspects taking advantage of a network of international collaboration and collaborations with the private sector. Importantly, this project is associated to a
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, Neuroscience, or a related field. A strong background in functional neuroimaging with experience in decoding and/or encoding models is required. Candidates with experience with recurrent neural networks will be