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the use of crystallographic software and data processing pipelines Experience working with computation clusters and managing large datasets Proven ability to develop, maintain, and optimize scientific
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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of hyperdimensional computing and vector symbolic architectures (VSA). As a Senior Research Engineer, you will: Implement, optimize, and run simulation code in Matlab and Python. Develop lab assignments for upcoming
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are not limited to models and algorithms for knowledge discovery, novel algorithmic and statistical techniques for big data management, optimization for machine learning, analysis of information and social
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and enhance grid resilience. This project aims to develop optimal coordination and control strategies for microgrids to achieve self-balancing when they are disconnected from the grids, and grid support
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feedstocks. ACCELERATE gathers leading academics and industries that want join forces. Within this effort, this position will focus on the engineering, analysis, and optimization of catalytic reactors
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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methods for optimized data analysis, Machine learning-based image segmentation of tomographic data (e.g., synchrotron X-ray microtomography), Design and use of autoencoders (VAEs, GANs), diffusion models
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Experience working with computation clusters and managing large datasets Proven ability to develop, maintain, and optimize scientific software Experience with scientific data visualization and related tools
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learning, mathematical statistics, optimization, and robotics. Experience from programming in C/C++ or Python is also meritorious. Willingness to work in an inter-cultural, international, and diverse group