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computational skills, with experience in advanced data analysis and statistical methods Proficiency in computer programming, ideally in MATLAB, Python or similar tools for scientific data analysis and
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and/or NMR constraints 5. Identify protein-ligand interactions using structural and biophysical methods DEPARTMENT SPECIFIC KNOWLEDGE, SKILLS, AND ABILITIES*: ¿ Proficiency with a protein structural
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observational data, and compare the results with those from other emulators of similar datasets (e.g. Gaussian Process methods by the project lead). These results will inform the IPCC AR7, and adaptation and
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well as nuclear physics. This diversity of research topics allows us to connect fundamental questions about the particles and forces governing our Universe to energy-related research. The methods of our
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, as well as the way memory, trauma and history are entangled. Job description: In close coordination with the project management and the other project members, the computer-assisted analysis
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the entire population. The project utilises advanced statistical methods such as multilevel models (mixed models), fixed-effects models, cluster analysis, and sequence analysis. The selected researcher is
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 11 days ago
Post-doctoral Position In Medical Image Processing The Computer-Assisted Medical Interventions (CAMI) team at the TIMC laboratory (Grenoble, France) is seeking a highly motivated postdoctoral researcher
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Informatics (IHI), University of Minnesota, Twin Cities. Dr. Bayat’s team develops highly scalable and computationally accelerated medical imaging and analysis methods to assist in enhanced diagnosis and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 5 days ago
’ phase to the linear ‘ringdown’ phase is an open question. The progress made in this field over the last few years has provided an estimate of the magnitude of various non-linear effects in ringdown
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5 Sep 2025 Job Information Organisation/Company University of Luxembourg Research Field Engineering » Computer engineering Researcher Profile Recognised Researcher (R2) Country Luxembourg