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this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat of data-driven modelling
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. Your duties and responsibilities include: Development of a flood classification framework for flood type prediction Comparison of different ML algorithms in a sensitivity study Communication with
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 days ago
Hospitalization management, LISBOA2030-FEDER-00853500, financed by national funds through FCT/MCTES (PIDDAC Workplan: The tasks to be carried out focus on developing tools to support staff shift planning in home
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the simulator and sensors located in the operating room (3) Develop data acquisition algorithms and data processing algorithms within the simulator (4) Develop forecasting algorithms (5) Raise alerts in
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of the following objectives: Design and development of long dwell-time, distributed signal processing algorithms for improved target detection Design and development of signal processing techniques for enhanced
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predict the hair line. Design a classification algorithm to quantify the hair loss severity. Develop a mobile phone app as point of care for people with alopecia. Evaluate novel AI assessments using
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numerical modeling and validation of brain-inspired algorithms Develop circuit-plausible training and inference algorithms, and analyze their behavior in LTspice and Cadence Spectre Perform algorithm–circuit
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bioinformatics field. Developing specialized methods for automatic or semi-automatic, possibly visually aided evaluation and model selection of such algorithms. Developing tailored solutions to integrate domain
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learning. Your job In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g
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summary Join an international team developing scalable algorithms to solve numerical linear algebra challenges on supercomputers. Modern high-performance computing increasingly relies on hardware