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the PORTUGAL2030 Programme, under the following conditions: Work Plan and Objectives to Reach: The work to be carried out aims at the research and development of Computer Vision and Machine/Deep Learning algorithms
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wide-field surveys (ZTF, LSST, Argus). • Develop algorithms for low-latency multi-messenger searches combining gravitational-wave, gamma-ray-burst, fast-radio-burst, and optical detections. • Make
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satellite constellations [2]. This PhD aims to develop a comprehensive analytical and algorithmic framework for deterministic QoS guarantees in dynamic LEO satellite constellations. The research will pursue
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: abstractions for LLM-powered operators and task-specific execution harnesses; algorithms for quality-, cost-, and latency-aware workflow optimization; methods for validating and adapting LLM-generated workflows
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-Health division, where real-time videomicroscopy approaches enable tracking of living cells after irradiation and reconstruction of their lineages using the CellLineageTrack (CLT) algorithm. This method
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in e.g. qubit measurements and quantum error correction algorithms. The core responsibilities include modeling, simulating and designing components and chips for photonic and neutral atom quantum
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error-correcting codes, establishing fundamental performance limits, and building practical decoding algorithms and architectures. Your research will sit at the interface between the classical and quantum
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benchtop spectroscopy experiments; data analysis, quantifying sensitivity and performance of the technology, and formulating algorithms for automated data interpretation and reporting; completing relevant
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scheduling algorithms for fast control and reconfiguration of the optical AI compute clusters. Realize a small-scale compute cluster lab testbed to demonstrate and evaluate the performance of the innovative
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
Physical Sciences workshop at NeurIPS. December 2021. A. Ribes, R. Persicot, L. Meyer, J-P. Ducreux. *A hybrid Reduced Basis and Machine-Learning algorithm for building Surrogate Models: a first application