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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Monterey, CA, USA, 2019, pp. 199-207, doi: 10.1109/MASS.2019.00032. Responsibilities and qualifications As a Postdoc at DTU
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in process and systems development related to laser-based metal AM Familiarity with process sensors for laser-based AM methods Familiarity with design for AM and post-processing techniques Innovative
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will develop in the position; it is expected that you have previous experience on each of them: Develop and implement CFD models to simulate the behavior of PRO systems. Apply ML algorithms to optimise
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learning representations and improve their interactivity. Make AI explanations more understandable Machine learning algorithms often appear as complex black boxes and much research goes into visualizing
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
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Foundation Classes (IFC), and linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models during run-time Data processing, incl. artificial intelligence
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key responsibilities will include: Designing and implementing advanced LabVIEW and C++ based control software for our HS-DAFM platform Developing specialized signal processing algorithms and circuits
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence