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programme Reference Number AE2025-0605 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0605
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knowledge of R and Python programming languages in the areas of algorithmic trading and modelling of market risk; Specific Requirements other significant achievements (e.g., awards, scholarships) and
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languages in the areas of algorithmic trading and modelling of market risk; experience in creating or co-creating and implementing national and international teaching projects; experience in organizing and
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
focus on improving biosignal analysis through signal processing and advanced algorithms, identifying predictors of adverse outcomes, using biosignals to improve physiologic understanding and leveraging
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language processing, large language models, and speech analysis to conduct research on building algorithms for early detection of Alzheimer?s disease based on audio-recorded patient?clinician data. Contribute to prompt
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, quantum compilation techniques, and noise-aware algorithms for Rydberg architectures. Apply quantum optimization to real-world problems such as logistics, scheduling, and portfolio allocation, comparing
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. Drafting of technical reports and promotion of results (publications, conferences). Where to apply Website https://www.imt-mines-ales.fr/ Requirements Research FieldComputer science » Computer
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software architecture. Drive research and development of algorithms for natural language understanding, structured command generation, and domain-specific model adaptation or fine-tuning. Integrate NLP and
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-based reconstruction algorithms and image analysis pipelines. These approaches will provide highly efficient high-dimensional MRI image acquisition and reconstruction. We seek an enthusiastic and
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/algorithmic modelling. Experience with multidisciplinary IoT systems, including low‑power sensor networks and power‑constrained device architectures. Hands‑on experience with experimental testing in