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Field
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open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you will contribute: in the application of the developed
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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machine control theory Programming in MATLAB, Python, C++ Working knowledge of optimization theory Knowledge of vector calculus and linear algebra The candidate should submit a research proposal for the
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the topic, and good knowledge of relevant theory and methods are a must. We are seeking candidates who have proven skills to work in a team, as well as the ability to work independently and in a structured
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apply them to relevant processes in biomedicine and catalysis. Thanks to the synergy between disciplines as diverse as synthesis, spectroscopy and theory, the PhD students will be able to develop
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ensembles, in collaboration with theory groups from QuRIOUS network. Achieving this goal would represent the first demonstration of a continuous superradiant laser on a clock transition. The doctoral
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between disciplines as diverse as synthesis, spectroscopy and theory, the PhD students will be able to develop an understanding of chirality at the atomic level, enabling them to maximise its potential in
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: Master in physics, computer science or comparable fields Good knowledge of quantum theory, ideally quantum information theory Organizational and communication skills Ability to work independently in
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technology experts work together to build a framework on open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you
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doctorate Very good knowledge of quantum theory and solid-state physics Experience and interest in computer programming Pronounced organizational and communication skills Self-organized and independent work