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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 11 days ago
-PULSE addresses a key open question in responsible AI: can we design practical machine learning systems that satisfy strong privacy guarantees [1] and fairness [2] constraints simultaneously, without
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Freedom found on-line at https://www.usg.edu/policymanual/section6/C2653 . The University of North Georgia, a regional multi-campus institution and premier senior military college, provides a culture of
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices. Support grant applications
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/computer engineering, applied mathematics, computational biology, bioengineering, or a closely related discipline. Solid experience training and evaluating AI models. Proficiency in Python and ML frameworks
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: The Smart Manufacturing & AI Systems Engineer (KTP Associate) will work on: Data acquisition pipelines and IoT sensor integration Building machine learning models for forecasting, optimisation, and automated
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» Biological engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Application Deadline 30 Jan 2026 - 23:59 (Europe/Lisbon) Country Portugal Type of Contract Other Type
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship