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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 2 months ago
datasets, the development of machine learning models, and performance evaluation in industrial application scenarios. Where to apply Website https://pica.cineca.it/unipd/ Requirements Additional Information
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process data locally while ensuring efficient and scalable artificial intelligence at the edge. TinyML and Edge AI have demonstrated the feasibility of embedding machine learning models on such devices
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of qualifications. Interview on: a) discussion on submitted qualifications and publications b) assessment of skills and knowledge in the field of: - Artificial Intelligence, Machine Learning and generative models
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look for correlations between transient phenomena in the ionosphere and seismic events. The successful candidate will develop and apply state-of-the-art machine learning techniques to enhance
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The position requires developing and implementing machine learning models
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Science Research unit: https://genomics.iit.it/ ESSENTIAL REQUIREMENTS PhD in computational biology, machine learning, bioinformatics, physics or related fields; High proficiency level in programming
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simulation, Digital Twins, Big Data, IoT/Web of Things, HCI, Edge/Cloud Computing, AI, Computer Vision, Machine/Transfer Learning, Computer Science Education, Computational Thinking, Formal Methods, Logic, Web
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validated nanoplasmonic sensing platform coupled with machine learning for the multiplexed analysis of prostate cancer (PC) biomarkers. Building upon our demonstrated ability to detect and classify ultra-low
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of renewable energy sources, with a focus on wind and solar power plants. By integrating meteorological observations, high-resolution numerical models and machine learning algorithms, highly accurate forecasts
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econometric techniques to develop descriptive statistics and estimate economic models. • Exploring machine learning techniques for handwritten text recognition. • Conducting literature reviews. • Assisting in