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encompasses various in silico modeling techniques to cover the multiple spatial scales, i.e. from molecular detailed to multicellular high-level regulatory networks, up to tissue level finite element models
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https
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models, handling of biological samples, molecular and cell biology techniques, omics data analysis, and scientific writing. LanguagesENGLISHLevelGood Additional Information Eligibility criteria Indicate
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model tunnel junctions, short-period superlattices, and III-V solar cells on silicon. Grow nanostructures, tunnel junctions, and solar cells using molecular beam epitaxy (MBE). Process the grown materials
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Materials group (NANOSFUN) is a research group of the Catalan Institute of Nanoscience and Nanotechnology (ICN2) that focuses on the research and development of novel molecular and polymeric functional
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LevelPhD or equivalent Skills/Qualifications The selected candidate will perform the following duties: - Experimental: generation and management of organoid models derived from patients, performance of high
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Postdoctoral Researcher position at the Laboratory of Metabolism and Obesity, led by Dr. Josep A. Villena. The research of Dr Villena’s laboratory focuses on the study of the cellular and molecular mechanisms by
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https
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machine learning models that predict soil health and crop performance. The position will exploit datasets integrating biochemical and molecular soil parameters (with a focus on microbiome features from
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Infrastructure? No Offer Description Research line: Learning in single cells through dynamical internal representations. Job description: Develop theory, models and algorithms for identifying molecular encodings