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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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Council to establish a center of excellence: Center for modeling adaptive mechanisms in living systems under stress. We are now opening a tenure-track Assistant Professor position in machine learning with
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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, Communications Engineering, Integrated Electronic Systems, Electromagnetics and Nanoelectronics, as well as Intelligent Systems and Machine Learning. We are now looking for a new Doctoral student for work in a
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to establish a center of excellence: Center for modeling adaptive mechanisms in living systems under stress. We are now opening a tenure-track Assistant Professor position in machine learning with employment
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are now opening a tenure-track Assistant Professor position in machine learning with employment at the Department of Computing Science. The position offers an opportunity to establish your research group
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, reliability, model-based AI, machine learning, and semantic or task-driven methods, within the group’s established research agenda. About the division and department At the Department of Electrical Engineering
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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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architecture, parallel systems, programming language theory, embedded systems or software engineering. Documented ability to teach operating systems and compiler construction. Practical experience of systems