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Join the forefront of groundbreaking research atCity of Hope where we're changinglives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our
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research direction is the integration of strategic transport models, such as discrete choice modelling (DCM) with agent-based modelling (ABM), to examine potential transport behaviour under different
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these methods across different crops to identify conserved patterns of stress resilience 4. Identify candidate genes associated with key agronomic traits related to resilience 5. Contribute to software and web
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related field. You have a strong background in numerical modelling and programming (preferably Python). You will collaborate with colleagues who are AeoLiS and CFD specialists, so affinity with
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Information Engineering Machine Learning and Data Science Embedded Systems and hardware-oriented development Modeling and simulation of complex systems Experience with Python, MATLAB, and/or C/C++ Strong
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) these effects can contribute significantly to local dynamics and their contributions are often under-estimated using global models. Previous work has shown that ionospheric mesoscale flows vary at different
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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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software that allow time-evolving models of complex systems to be calibrated against sparse, indirect, and uncertain observations. The group develops and maintains an open-source Python framework
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the neurobiological foundations of language and auditory processing, with a particular focus on individual differences, multilingual and multiliterate experience, language aptitude, dyslexia, brain anatomy and
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performing research as exemplified by first-authored peer-reviewed publications. Knowledge, Skills & Abilities: Data analysis skills, including data visualization in IDL or Python. Scientific writing, as shown