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Field
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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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help develop and characterise advanced patient-derived tumour models and use them to test promising therapeutic targets that exploit vulnerabilities caused by loss of the SMARCB1 gene. This role offers
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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model for communities worldwide facing similar 21st-century challenges. This is a fixed-term position for one year with the option to renew for a maximum of two years. UT Austin offers a competitive
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variety of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and theories. Develops advanced analytical models and systems and provides solutions and
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R
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problem formulation from solution concepts, integrating models from different disciplines, operating at different time/spatial scales, analyzing the performance, and cost/schedule/risk aspects of the system
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involves interdisciplinary research on the development and evaluation of large language models for low-resourced langauges, primarily focusing on Danish and other Nordic languages. The research will focus