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decomposed into modular sub-components that can be either process-based models and/or deep learning models. MCL has the flexibility to replace any uncertain process description with a deep learning model
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has: A PhD in translational and laboratory medicine within the field of IBD. Proven expertise in omics data analysis, including proteomics and metabolomics data (R/RStudio, multivariate and regression
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, materials science, and artificial intelligence. What we expect Applicants should hold a PhD in electronic engineering (the degree should have been completed within the last 5 years at most): Strong background
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collaboration with PI Associate Professor Mette Simonsen Abildgaard. Qualification Requirements • Applicants should hold a PhD in anthropology, STS, arctic studies, media studies or related fields
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Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
genome-scale and process-level models and contribute to comparative analyses across scales and experimental conditions. Postdoctoral researcher in experimental evolution of complex methanogenic microbiomes
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Postdoc position in modeling and analysis of cyber-physical systems At the Technical Faculty of IT and Design, Department of Computer Science, a full-time postdoc position in modeling and analysis
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a major research and education center based at Aarhus University hosting 60 senior scientists, ~100 postdocs and ~160 PhD students. The center combines expertise from the disciplines including physics
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candidate with: A PhD degree in Life Science, preferable Cell Biology, Biomedicine, or Computational Biology Curious mind-set with a strong interest in fundamental Cell cycle, DNA replication and Genome
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Postdoctoral Positions in PFAS Analytics, Degradation, and Thermophysical Properties - DTU Chemistry
computational determination of thermophysical and physical–chemical PFAS properties. PFAS molecules are defined by the presence of CF₂ or CF₃ groups and exhibit a wide range of unique characteristics, including
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learning–based), advanced mesh generation techniques for simulation, and experience with biomedical simulation, both virtual and physical. Experience with laboratory and clinical validation of models is