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experience with EB-PBF systems is considered an asset) Python programming Statistical learning / machine learning / machine vision / Artificial Intelligence methods Image and signal processing (familiarity
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of Mathematics and Natural Sciences at Heinrich Heine University Düsseldorf is inviting applications for the position of a Professorship for Machine Learning (open rank: W2 or W1 with tenure track to W2
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AI-based diagnostics for fleet-based condition monitoring of electric vehicle motors using machine learning frameworks (S3.5-ELE-Panagiotou) School of Electrical and Electronic Engineering PhD
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tasks and zero-shot evaluation in linguistic analysis. Profile • Master’s degree (M2) or PhD in computer science, NLP, machine learning, deep learning, or a related field. • Strong experience in machine
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processing using high-throughput experimentation (HTE), analytical tools and machine learning under CircuLab. The candidate will be dedicated to establish the unique functionality of the platform and should
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components. The resulting data will be used to train a machine learning (ML) model, enabling automated and efficient beamline alignment. This technology has the potential to significantly enhance
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yrs. of experience in field or PhD in field of expertise + 0-2 yrs. of experience in field Research Specialist, Psychometrics & Machine Learning Applications: $67,150 - $83,900; Master's in field
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Boston University Chobanian & Avedisian School of Medicine | Boston, Massachusetts | United States | 1 day ago
, sexual orientation, gender identity, genetic information, military service, or veteran status or any other characteristic protected by law. We are a VEVRAA Federal Contractor. To learn more, please visit
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academic goals with mutual respect and shared inquiry. The position supports research on forecasting agricultural production and yields using geospatial data, machine learning, and ground-based measurements
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consistency outside the training domain. This PhD research is envisioned to result in a breakthrough in the application of machine learning methods to fire engineering problems, by ensuring compatibility with