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Previous Job Job Title Postdoctoral Associate in Mathematical Foundations of Generative AI Next Job Apply for Job Job ID 375806 Location Twin Cities Job Family Academic Full/Part Time Full-Time
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engineering, control engineering, operations research, applied mathematics, or a closely related field. Documented experience in energy-system modelling, mathematical optimization, control, digital twins
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, evaluated, and optimized for a seamless continuum of education. The Teaching Academy of the TU Delft has identified this integration, engineering students’ progression and retention of knowledge & skills, as
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energy-system modelling, mathematical optimization, control, digital twins, or related areas. Strong programming and numerical modelling skills using Python, MATLAB/Simulink, Julia, hardware in the loop
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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experience with tabular or heterogeneous data, particularly across multiple da-tasets, domains, or tasks Is familiar with mathematical optimization methods, such as mixed-integer linear programming Has
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. To conduct this work, the successful candidate will use the world's first exascale system, Frontier, and collaborate with leading experts in machine learning, optimization, electric grid analytics, and
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analysis of large datasets (e.g., bioinformatics, computational biology, data science, computer science, computer engineering, electronics, biostatistics, mathematics, physics, biomedical engineering, or
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Do you have a strong mathematical background in geometry or numerical analysis? Are you inspired by applications to engineering, physics, or industrial problems? Do you thrive in a multi
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materials. The focus is to develop novel electrochemical deposition methods, control interfacial reaction kinetics, and engineer functional coatings and thin films. Advanced process design and optimization