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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 1 day ago
them to work on innovative research topics and to develop and apply the scientific methods appropriate to their research topics. Course organisation During the three-year programme, doctoral students
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested developing new machine learning methods for precision medicine and
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years [1], we are in great need of alternative, energy-saving methods of calculation, so that the large-scale rise in AI does not lead to widespread disillusionment. In addition, embedded systems
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human perception and cognition. Experience in: experimental methods, computer rendering or VR/XR, programming. Affinity with multidisciplinary work, combining science, art, and technology. Enthusiasm
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application! We are looking for up to two PhD students in trustworthy machine learning, with a particular focus on cybersecurity, privacy, and verifiability for AI systems, based at the Department of Computer
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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5 Sep 2025 Job Information Organisation/Company University of Luxembourg Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country Luxembourg
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/cancer-related work, advanced training courses (e.g., methods of data analysis and statistics, animal experimentation license, etc), participation in scientific programs, etc Education and training Have
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: - Optimization of solid phase extraction of pharmaceuticals occurring in environmental matrices; - Development and validation of analytical methods based on liquid chromatography coupled to mass spectrometry
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computational modelling with experimental validation. The project involves developing time- and position-dependent models of electrochemical double layers, and parameter estimation methods incorporating