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Field
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Responsibilities: Conduct in-depth research in sublinear time and learning augmented algorithms. Design, develop, and implement novel algorithms and models. Publish research findings in leading international
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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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progression once in post to £48,149 Grade: 7 Full Time, Fixed Term contract up to March 2028 Closing date: 13th August 2025 Background This research project aims to establish the theoretical and algorithmic
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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. Interest in clinical algorithm development and dexterity with biostatistical coding in R or Python is a plus. The primary goal of this aspect of the CH CARE Study is to combine serially obtained somatic and
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intelligence algorithms.”, financed by National public entities (IFAP IP), under the following conditions: Scientific Area: Geospatial Engineering Admission requirements: Candidates must meet the following
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algorithms. Analyzing results and contributing to scientific publications in peer-reviewed journals (expected 3 papers), presenting at meetings and international conferences. Taking part in the teaching as
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- “Data-driven algorithms for multi-product inventory systems with non-stationary demand”. Qualifications Applicants should have:- (a) a doctoral degree, preferably in the area of operations management