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numerical models to improve the simulation of complex multiphase phenomena. The study will combine theory, algorithm development, and computational modeling, with the goal of advancing scalable hybrid
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modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring of individual cows. The work includes
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exploratory analysis on large, multi-dimensional datasets; (b) develop predictive/diagnostic models and algorithms to lead and support clinical/translational research; (c) collaborate with cross-functional
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Requirements Knowledge of advanced concepts in information processing using machine learning algorithms LanguagesROMANIANLevelGood Research FieldComputer scienceYears of Research Experience1 - 4 Additional
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the project activities. – Assist in the dissemination of project results through presentations, publications, and stakeholder engagement. Development of algorithms (80%) – Conduct a comprehensive review of the
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measurements Calibration of materials as sensors to measure temperature, oxygen, and pH values in cells Development of models based on artificial intelligence algorithms to interpret luminescence signals Study
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 15 days ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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. Responsibilities: Develop GPU-accelerated dose calculation and optimization algorithms for adaptive HDR brachytherapy. Integrate real-time adaptive planning capabilities into an in-house treatment planning system
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, real-world grid data. Your tasks in detail: Design a framework to distribute a distribution grid Develop a distributed version of an existing Bayesian Distribution System State Estimation algorithm
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Offer Description Your Responsibilities Qualitative analysis of choice architectures and recommendation algorithms of social media platforms in the context of their communicative function within