36 postdoctoral-machine-learning PhD positions at Technical University of Denmark in Denmark

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PhD scholarship in Machine Learning for Scenario Discovery in Complex Urban Mobility Systems - DTU Management PhD scholarship in Forecasting Bioplastic Degradability with Machine Learning - DTU Sustain PhD scholarship in Automated Machine Polishing of Complex Mould Geometries - DTU Construct PhD scholarship in Automation of Tool Wear Measurement and Data Driven RUL Estimation for Sustainable Machining Operations - DTU Construct

Technical University of Denmark | Denmark | 29 days ago

driven RUL estimation for sustainable machining operations”. Nowhere in the text, it is explained what the abbreviation RUL stands for. The position is funded in the context of the project MADE React co
PhD scholarship in Time-Predictable Computer Architecture - DTU Compute PhD scholarship in Deep Learning Theory and Differential Geometry - DTU Compute DTU Tenure Track Researcher in Computer Vision and AI for Wind Turbine Components - DTU Wind PhD scholarship in Additive to Predictive Manufacturing for Multistorey Construction using Learning by Printing and Networked Robots (AM2PM) - DTU

Technical University of Denmark | Denmark | 2 months ago

also be able to demonstrate excellent ability to code with or learn computer programming languages, such as C++, C#, Python, and/or Matlab. A desire to engage in cross-disciplinary research
PhD scholarship in AI Solutions for Renewable Power System Stability Assessment - DTU Wind

Technical University of Denmark | Denmark | about 7 hours ago

Job Description Are you passionate about renewable energy and eager to apply machine learning to real-world challenges? Join our research team at DTU and work on groundbreaking advancements in
PhD scholarship in Development of Simulation for the Fatigue Life Prediction of AM Components based on Process-Induced Defects - DTU Construct

Technical University of Denmark | Denmark | 5 days ago

collaborate closely with a postdoctoral researcher responsible for in-situ fatigue testing under corrosive environments, and will participate in the 4D (x,y,z,time) analysis of the AM microstructure and crack

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