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shadows Strong mathematical education, in particular in relation to linear algebra Programming experience is a plus Ability to effectively communicate in written and spoken English Ability to work
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., linear algebra, statistics, optimization, and calculus) is expected, along with programming experience using deep learning frameworks in Python (e.g., PyTorch). While prior knowledge of machine learning
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particular in relation to linear algebra Strong programming experience Ability to effectively communicate in written and spoken English Ability to work autonomously and in close interaction within a team Most
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members and with other faculty at MPIM, such as Number Theory (Blomer, Harder, Moree), Arithmetic Geometry (Faltings), Modular Forms (Zagier), Teichmueller Theory (Hamenstaedt), Complex Algebraic Geometry
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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information (e.g. tensor network calculus, quantum communication protocols, quantum tomography protocols), linear algebra, and programming (e.g. Mathematica/ Python/ Matlab). You have an excellent command
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. The Mathematical Institute has four research themes: Algebra, Geometry and Number Theory; Analysis and Dynamical Systems; Probability Theory; and Statistics and Data Science. LIACS concentrates on the study of
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: religious meaning-making in language use Cosmic Interacting Matters From Atoms to Turbine Blades Symplectic Structures in Geometry, Algebra and Dynamics Bulk Reaction – reacting and moving granular assemblies
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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structures, etc to solve challenging problems is required (there will be a practical coding assessment during recruitment) A solid mathematical foundation is required (multivariable calculus, linear algebra