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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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. Such multimodal energy sources will become increasingly vital over the next decades, not only as sources of renewable energy but also for high-tech applications, such as powering unattended wireless sensors
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tasks Further development of the sensor based on aerosol separation technique and field effect transistor Use aerosol measurement technique, electron-beam lithography and cleanroom equipmen Design of
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programming and know how to use version control. ▪ You are experienced in the usage of machine learning (e.g., Actor-critic algorithms, deep neural networks, support vector machines, unsupervised learning
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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable
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study qubit systems. A particular emphasis is on exploiting the manipulation capabilities of scanning probe microscopes to fabricate molecular quantum sensors on probe tips to detect the tiny electric and
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the environment, including traffic conditions, travel time, and cost. The project will define the DRL components (states, actions, rewards, policies), select and implement suitable DRL algorithms, and integrate