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Field
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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independent and collaborative research in electromagnetic sensor systems, including theoretical analysis, numerical modeling, AI-assisted sensing algorithm development, and experimental validation
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processing, beamforming, image reconstruction, elastography, Doppler imaging, or computational imaging. Demonstrated experience in algorithm development and scientific programming, preferably in Python
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evaluating their performance relative to classical machine learning and statistical methods. The research would combine algorithm development with implementation and evaluation on current quantum computers
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environment. REQUIRED : Ph.D. in computer science, mechanical engineering, applied math, or related field with significant research experience in machine-learning/AI algorithm development, specifically in
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computational methods, working with large and heterogeneous datasets, evaluating algorithm performance and uncertainty, and translating research methods into reproducible scientific software and analyses. The
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focuses on algorithm development, data fusion, and deployment for anomaly detection in solar panels and battery systems. Key Responsibilities Develop computer vision and deep learning algorithms
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provisions of the WissZeitVG, the duration we can offer may differ in individual cases). The start date is October 2027. Heidelberg University stands for equal opportunities and diversity. Qualified
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Research experience that includes medical image processing, Artificial Intelligence (AI) algorithm development, and scientific writing. Gain clinical experience including training in radiation oncology