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programming task within the thematic context of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bi-molecular-machine-learning/ Employment conditions This is a
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion phenomena and link speciation with
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used
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) The Institute of Computer Engineering (ZITI) at Heidelberg University invites applications for one research assistant position with the possibility to do a PhD in parallel at the chair of computer architecture
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy