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Field
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Join our team as a Early-Career PostDoc (m/f/d) in the research area of AI‑based modelling full-time (39.2 hr/week), fixed term for two years. Leibniz-IWT stands for research in the field of new
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learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques
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and publications. Required Qualifications • PhD in Mathematics, Engineering, or a related field with a background in statistical and mathematical modeling. PhD must be awarded no more than four years
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in applied mathematics, field methodologies in unconsolidated sediments and/or numerical modeling is preferred. Candidates should have a publication record in hydrogeology and/or related fields
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. The project seeks to advance population health using innovative quantitative methods in system dynamics computational modeling and structural equation modeling applied to accelerating the translation and
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to self-organize into complex structures. Our approach is to develop sophisticated mathematical models – informed by state-of-the-art biological knowledge and experimental data – to understand
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Applications are invited for a Research and Innovation Associate in the atomic astrophysics group, Department of Applied Mathematics and Theoretical Physics, University of Cambridge. The successful
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A position exists for a Postdoctoral Research Associate in the Department of Applied Mathematics and Theoretical Physics modelling the decontamination of porous and absorbent material. This project
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed
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techniques may be employed to support the modeling of uncertainty, along with the formulation and resolution of planning problems using stochastic optimization methods. Key Responsibilities The selected