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and optimize robotic software systems using Python and C++. Create and manage simulation environments tailored to specific robotic applications. Work with ROS (Robot Operating System) for robot control
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description and working tasks Linear algebra expressions are evaluated in an efficient and robust way by mapping them to a carefully chosen sequence of calls to optimized functions as offered by libraries
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macromolecular modeling: Investigate electronic, optical, molecular, and transport properties of soft materials, including conductive and semiconductive polymers, biopolymers, and macromolecules, to optimize
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the problem is explicitly considered. In particular, it will investigate how to tightly integrate state-of-the-art sampling-based methods with state-of-the-art methods from numerical optimal control in a
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computational methods for design, dimensioning, sensitivity, robustness, optimization, automation, feedback control, etc. Development of process engineering applications that demonstrate model-based methods but
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part of the MARTINA project and will explore the application of co-design optimized machine learning and neuromorphic solutions for applications that are challenging to address using conventional
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central role in streamlining and standardizing the design flow for quantum device fabrication. This includes implementing and improving design rule checks (DRC), optimizing and debugging code, and
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application no later than August 1, 2025. Project description Linear algebra expressions are evaluated in an efficient and robust way by mapping them to a carefully chosen sequence of calls to optimized
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research in advanced computing solutions for 6G wireless networks. This includes the development, integration, and optimization of Kubernetes for specialized hardware platforms. You will actively engage in
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genetic data (e.g. from genotyping). You will implement and evaluate selection methods: Test and optimize new methods for precision breeding in practical or simulated improvement programs. You will work