407 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship positions
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). Proficiency with programming languages (e.g., R, Python, Matlab) for data management and analysis, computational social science, and/or machine learning applications. Acquisition, processing, and analysis
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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R
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Machine Learning components of the CONVERGE project toolset.; - Assist in executing integration tests across different hardware and software modules.; - Contribute to the structured collection and
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of extrusion systems, reinforcement strategies, construction detailing, and construction scale experiments. RA3) Machine Learning and Optimisation for Digital Construction: Data-driven and simulation-based
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fields. Relevant Training or Courses (optional): Experience with R or similar programming tools, or machine learning algorithms. Geographic Information Systems (GIS). Basic and advanced statistics, time
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Engineering/ Electrical Engineering. 2. Admission Requirements: Bachelor's degree in Computer Engineering, Systems and Information Technologies Engineering, Electrical and Computer Science Engineering, or in a
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a current curriculum vitae, research statement, and a cover letter. Contact information for three references is required. To learn more about AI at Princeton, please visit https://ai.princeton.edu
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate
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) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Development of novel Machine Learning techniques applied in systems/networks research, which includes, but is not