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Field
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comprise all aspects of applied mathematics, from model development and mathematical analysis to numerical implementation and statistical estimation of models as well as software packaging. What to expect
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will contribute to projects focused on developing advanced machine learning models to quantify phenotypic traits of crops, including corn, soybean, and other selected species. These models will leverage
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well as emerging materials. These experimental techniques will be complemented by advanced electromagnetic modelling. Responsibilities and qualifications The ideal candidate will possess demonstrated expertise in
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for Bioengineering of Catalonia (IBEC) is seeking a highly motivated Pre-doctoral Researcher to join an exciting PhD project focused on modeling human tauopathies. The successful candidate will work with mouse models
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patient outcomes. Structured around three core scientific pillars—regenerative medicine, biomaterial science, and translational research models—SHIELD supports research on therapeutic strategies, novel
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- and micro-flow LC-HR-MS/MS for comprehensive multi-omics analysis. Proficiency in Python and R (essential) for data analysis, modeling, and visualization. Ability to work effectively within diverse
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in genome and exome sequencing analysis. Expertise in bulk and single-cell RNA sequencing analysis. Proficiency in programming languages such as Python and R for data analysis, modeling, and
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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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researchers addressing complementary topics and methodology such as Thermodynamic modelling of multi-component planetary degassing/ingassing, Molecular Dynamic simulations of silicate melts, Petrology
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training