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-resolution dosimeter, and new algorithms. Following this, the candidate will parameterize a Monte Carlo-based dose calculation system (e.g., GATE, TOPAS, or Geant4-based simulation tools) for evaluation in
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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or accelerated acquisition and reconstruction algorithms will be highly valued. Instructions Interested candidates should apply via Interfolio link with their CV (including a full list of publications), a
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, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing
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strong interest in machine learning and deep learning algorithms · Research and publication experience in health outcomes research Application Materials: · CV · Cover letter · Contact information for three
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of concepts from quantum information to quantum materials; algorithmic aspects of quantum computing; topological aspects of magnetism; connections between condensed matter and high-energy physics
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Science and Engineering, or a related area is required. The position will involve developing models and algorithms for the evolution of inorganic aerosols in the atmosphere, building upon the research
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will