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aspects of research, conducting field research and development of physics guided machine learning models. The primary project focuses for this Part Time Research position deepening the understanding
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biological environments - Experience using machine‑learning algorithms for luminescence signal analysis and sensing applications - Experience writing scientific articles and presenting results at conferences
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. The manager will develop an annual work plan in consultation with the two supervisors and is evaluated on the success of that plan. The Department of Engineering Education (http://www.enge.vt.edu) is home to
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, proteomics, metabolomics), Capacity to develop and/or apply : Statistical or mathematical models Machine learning / AI methods Systems biology modeling approaches Research position The fellow will conduct
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(PDE). Examples of models in the scope of the project include particle models, stochastic PDE and models from fluid dynamics and machine learning. Place of work is the Department of Mathematics, Blindern
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and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine Learning as well as an ability to develop, build and test interactive
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emerging spectrum (FR3, MMW, sub-THz/THz) Extreme massive MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless
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physiological signals, with a focus on ECG, and to develop machine learning and deep learning methods for classifying clinical, health, and wellness findings. Supporting project management and research group
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pangenomics), quantum-based simulation methods for drug design, or quantum machine learning for large omics datasets. The candidate is expected to have acquired first teaching experience, and first experience
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The project will prioritise digitising these records using natural language processing (NLP) and machine learning (ML) to create structured datasets. These will support AI applications in paediatric care