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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 25 days ago
– Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD Student (f/m/d) in Quantum Algorithms for Droplet and Bubble Oscillation Dynamics
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eligible for, including health insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link: https
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or integrate with larger epidemiological databases You are experienced in machine learning models to interpret complex data types The official administrative language used at KU Leuven is Dutch. If you
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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; Visual Computing, Medical Informatics, and Bioinformatics; Web Intelligence and Recommender Systems; Computing Education; Interactive Machine Learning; Cybersecurity and Adversarial Machine Learning
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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and adapt machine learning and deep learning models (e.g., convolutional and transformer-based architectures) to biological questions in collaboration with investigators. Develop interpretable models
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro
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Software Engineering. Find out more about SoC at https://www.cdm.depaul.edu/academics/Pages/School-of-Computing.aspx . Qualifications: Minimum requirements include a PhD degree in the discipline, or a
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse