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data sets, which have to be evaluated in order to obtain a holistic understanding of very complex systems. Visit HDS-LEE at: https://www.hds-lee.de/ The position is placed at the Institute for Advanced
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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isotherm parameters directly from molecular properties. These predictions will be integrated into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use
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. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a strong background in applied mathematics Excellent programming skills (Python, C/C
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software openly with documentation. Your Profile: A Masters degree with a strong academic background in mathematics, computer science and earth science/engineering, or a related field Proficiency in at least
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, computer science and earth science/engineering, or a related field Proficiency in at least one programming language (Python, Matlab, R, C++, Julia, …) Good analytical skills with a sound understanding of data
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domains: life and medical sciences, earth sciences, energy systems, or material sciences University degree (M.Sc. or equivalent) in applied mathematics or in computational engineering science
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, computer science, physics, material science, earth science, life science, engineering, or a related field Proficiency in at least one programming language (Python, R, C++, Julia, …) Good analytical skills with a
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submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and regression models to isolate task-related submanifolds and their respective role for sensory processing and task