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Field
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Processing and Machine Learning to develop signal processing and machine learning algorithms and methods for communication networks. Key Responsibilities: Develop signal processing and machine learning
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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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advances the mathematical foundations, algorithms, and real-world applications of epistemic uncertainty in machine learning, with a strong focus on imprecise probabilities, uncertainty representation and
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. (Required) Familiarity with modern data acquisition equipment, associated technologies, sensors, interfaces, analysis tools, software, and scientific programming languages (e.g., Python) used in instructional
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performance metrics using social media management platforms. Stay up-to-date with the latest social media trends, algorithms, and best practices to ensure our content remains fresh and exciting. Actively engage
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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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employment This is a 7-month position from October 1st, 2025, or as soon as possible. Job description You will participate in the ongoing development of an algorithm platform for digital shadows and twins
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the areas of ‘Process Sensors and Systems Engineering’, ‘Material Analytics’ and ‘Computational Methods’. With our expertise in data science, modelling and systems engineering, we develop tailor-made
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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