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Field
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of the stock structure of many fish populations in the Baltic Sea is limited. For numerous species, we lack detailed knowledge about changes and spatial variation in migration patterns, reproduction, size and
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experience in many-body quantum theory and/or quantum computing. Experience with numerical methods or quantum simulation frameworks. Preferred Qualifications FLSA Exempt Full Time/Part Time Full Time Number
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and laboratory-based methods to investigate the long-term frequency and magnitude of historic and prehistoric earthquakes and tsunamis at the Cascadia, Alaska, and Chile subduction zones. The data
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and of research methods and techniques to work within established research programmes. Applicants should be able to demonstrate a successful track record in clinically-relevant psychological research
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
related field # Proficiency in programming languages (Python, C/C++, Julia) # Background in machine learning methods # Experience in developing, training, and tuning machine learning models # Prior exposure
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, aerodynamic, and aeroelastic testing. Develop and apply advanced numerical models (e.g., FEA, CFD) to simulate wind effects on structures. Analyze and interpret experimental and numerical data, and disseminate
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of reactor systems. Knowledge of heat transfer and fluid dynamics for nuclear system applications and reactor safety analyses. Knowledge of computation methods and numerical solvers for engineering
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critical role in advancing computational materials science by developing and applying first-principles and machine learning methods, with a focus on interatomic potential development and large-scale
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of the project Bacteria are constantly predated by viruses, bacteriophages. To resist predation, bacteria employ numerous antiphage defence systems, with the most famous being CRISPR-Cas. In our lab we discover
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that integrate simulation, machine learning, and data analysis. Numerical optimization methods (e.g. machine learning including deep neural networks, reinforcement learning, data mining, genetic algorithms