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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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, this project aims to establish new knowledge on how microbial proteins can be optimized and integrated into hybrid foods of the future. About us The Department of Life Sciences aims to bridge cutting-edge life
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to ensure optimal tissue concentrations during surgery. The PhD student will utilise national and international arthroplasty registry data, adapt in vitro diagnostic tools such as the Minimum Biofilm
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. Strong machine learning fundamentals (probability, statistics, optimization) and strong interest in time-series modeling and physics-guided machine learning. Proficiency in Python and modern deep learning
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the Climate Compatible Growth project, funded by the UKAID/FCDO. The ultimate goal of the effort is to deduce the potential for AI to aid in determining the most influential factors for (cost-) optimal
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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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projects from low level hardware interfaces to high level optimized applications mainly in Python and under Linux Increasing the functionality and reliability of the beamlines in order to realize
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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