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contribute to our interdisciplinary research efforts. The candidate will be instrumental in designing, developing, and programming advanced DNNs and AI algorithms. The focus of the research will be
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: Demonstrated experience in clinical research methodologies, including study design, patient recruitment, data collection, and compliance with regulatory requirements Medical Knowledge: Strong understanding
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researcher, funded from the project PNRR I8 „AI design of decentralized coopetitive control over networks - DECIDE”. The position concerns the development and analysis of techniques for nonlinear and networked
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novel machine learning (ML) and artificial intelligence (AI) instruments for pattern extraction, explanation, and forecasting of the high-dimensional, non-stationary, temporal data encountered in energy
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the Towards high project -throughput biosensors with increased sensitivity and specificity (BIOSENSE)" - CF 129/31.07.2023, financed by the National Recovery and Resilience Plan (PNRR). Requirements
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community, Innovation Capacity: • An innovative attitude and creative thinking to develop new methods and tools. Research Ethics: • Deep understanding of ethical principles in research and commitment
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advantageous if candidates demonstrate publications in non-Gaussian stochastic modeling in journals relevant to the scientific community. Innovation Capacity: • An innovative attitude and creative thinking
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is considered advantageous if candidates demonstrate publications in non-Gaussian stochastic modeling in journals relevant to the scientific community. 3. Innovation Capacity: • An innovative attitude
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sustainability, in journals relevant to the scientific community. Innovation Capacity: • An innovative attitude and creative thinking to develop new methods and tools. Research Ethics: • Deep understanding
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stochastic modeling in mathematical finance, in journals relevant to the scientific community, Innovation Capacity: An innovative attitude and creative thinking to develop new methods and tools. Research