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analysis, with the long-term goal of enabling health-aware battery management and optimized charging strategies. Qualifications Requirements A doctoral degree or an equivalent foreign degree in Control
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
optimization. Participate in collaborative research projects and mentoring. Contribute to academic publications, reports and seminars The selected candidate will be part of the Foundations Cluster of CIDSAI and
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization
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for acoustic metamaterials/metasurfaces; use simulation and data-driven optimization; contribute to listening tests and VR-based soundscape evaluation; build or test prototypes; publish results; and contribute
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-throughput data, identify differentially expressed genes, explore protein interaction networks, and perform pathway and functional enrichment analyses. Responsibilities also include developing and optimizing
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AI-driven decision making. It will be conducted in collaboration with the Automatic Control group (from Department of Electrical Engineering) and the Mathematical Optimization group (from Department
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techniques such as cloning, PCR, mutagenesis, DNA extraction, gel electrophoresis 4. Knowledge of protein/antibody discovery and optimization using in vitro display (such as phage or yeast) technology 5
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polymerization techniques; 2) development and optimization of protocols for the preparation of nanoparticles; 3) evaluation of the unique properties and functionalities of the developed biomaterials. This position
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method development and large-scale research facilities. Essential Duties and Responsibilities Develop workflows to improve models and maps to optimize likelihood for ligand placement Develop AI/ML methods