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for energy saving purpose. The role will focus on geometric representation, multi-physics numerical simulations, machine learning and manufacturability constrained design optimization given metal additive
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-driven Proteoform-based Drug Repurposing for Targeted Cancer Therapies DC11: RNA Methylation Gain as a Mechanism of Resistance to Therapy in Myelodysplastic Syndromes DC12: Optimization and Preclinical
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project on the development of smart optical sensors for environmental monitoring in the oil & gas industry. Our photonics research lab has set modern tools for the design, testing, and optimization
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previous work to channel flows, both with and without wall roughness. The research will focus on, firstly, optimal synchronisation of minimal unit turbulence (MUT), leveraging the simplified dynamics in MUT
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numerous projects financed from domestic and foreign funds annually, the goals of which are to increase the innovation of the Polish economy. Job Responsibilities: Implementation of technological processes
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC-Chapel Hill offers full-time
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practical applications of advanced machine learning techniques. Emphasis will be given to theoretical approaches in machine learning for real-world applications, with a preferred focus on optimization, data
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, such as pulse design or numerical optimization Background in data-driven or machine-learning approaches relevant to optimal control (e.g., model learning, reinforcement learning) What you will do Take
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, thrive in a dynamic environment, and want to be part of a team that drives meaningful impact, we’d love to hear from you! Join us and be a part of shaping the future of finance at NUS! Website: https
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chair (F Schwenninger) within the cluster “Mathematical Analysis, Geometry, Numerics and Systems” (MAGNUS) of the Department of Applied Mathematics. The project “Optimal Constants as Analytic Benchmarks