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, networks and communication systems, theory of computation, computing paradigms, AI and machine learning, numerical computing, and applied computing. In particular, beyond surveying individual fields and
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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at the CCA include: Astronomical Data, Stars & Plasma Astrophysics, Galaxy Formation, Gravitational Wave Astronomy, Cosmology, Machine Learning & Astrophysics, Exoplanets & Planet Formation, Astronomical
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of immune cell function. These projects are focused on making safer and more effective cell therapies (e.g., CAR-T) and gene therapies for cancer and beyond. We are an interdisciplinary lab spanning
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. Integration of Artificial Intelligence and Remote Sensing Science: machine-learning / automated analysis of large datasets, calibration and validation, feature extraction, image processing and classification
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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should hold a Master's degree in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, or a closely related field Solid background in machine learning and natural