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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | about 17 hours ago
that enables them to work on an innovative research topic and to develop and apply the scientific methods appropriate to their research topic. Course organisation During the three-year programme, doctoral
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on the analysis of complex event history data, with some relevant topics being the analysis of outcomes under competing risks, studies of individual heterogeneity, estimation using machine learning methods and
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 17 hours ago
neuroscience and cognition to the development of novel methods in neuroimaging, computational neuroscience, and artificial intelligence. To cover this spectrum and provide top scientific quality, the IMPRS CoNI
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particle physics phenomenology -programming in C++ and/or Python -fluent knowledge of English language Welcome: experience in Monte Carlo methods and statistical modeling experience in QCD phenomenology
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23 Jan 2026 Job Information Organisation/Company ETH Zürich Research Field Computer science » Computer architecture Computer science » Programming Computer science » Other Engineering » Biomedical
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have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput
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the application and theory of electromagnetic geophysical methods, especially magnetotellurics Sound computer skills in Windows and Linux Demonstrable, sound programming knowledge and experience in at least one
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plant research and methods including growth analysis and gas exchange measurements Knowledge and/or interest in whole plant physiology (from soil to plant) Good computational skills and a working
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of these findings into future dietary intake estimates. This work will involve the use and optimization of advanced analytical tandem mass spectrometry methods, assessment of vitamin D bioaccessibility using an in
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the flexibility of neural methods. If successful, the work has the potential to advance applications such as automated theorem proving, knowledge-graph inference, and causal analysis. The Department of Computing