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Position Title: Postdoc Research Associate in Machine Learning Appointment Type: Post Doc/Trainee Job Description: Summary of Duties and Responsibilities: This position will involve developing
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Application documents: 1) Brief cover letter, explaining your motivation for applying, 2) Detailed curriculum vitae (including your email address), 3) Complete transcript of grades from all your university-level studies. We do not ask for more information/documents at this point (but you can...
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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SUSTECH – Accelerating Sustainable Technological Trajectories with Computational Chemistry and Machine Learning. Where you will be: The position is hosted by the research group Technology and Innovation
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Synergy Grant project SUSTECH – Accelerating Sustainable Technological Trajectories with Computational Chemistry and Machine Learning. Where you will be: The position is hosted by the research group
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Models, Knowledge Graphs, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the following areas: Natural Language Processing, Knowledge Graphs, Machine
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& Immunology (MMI). Provides high level HR administrative, and organizational coordination and support for MMI Postdocs, staff, students, & faculty level positions. Serves as a primary point of contact for ISSS
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statistical physics, control theory, and where appropriate, machine learning and data-driven techniques. The position offers a structured career development path within an active and ambitious research group
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development of empirical and AI-based evaluation methods (e,g, machine and deep learning) and/or process-based models in the field of remote sensing (e.g. radiation transfer models) and for provision of input
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Assistant Professor position in Computer Science with a Focus on Interdisciplinary Data Science_3...
enable advanced analytics across disciplines. Experience in developing and deploying machine learning solutions is considered an advantage. Experience applying such solutions within digital humanities