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Field
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the content of the science they study. You will be an active member of RCNP. You will collaborate with the other postdoctoral researchers, PhD candidates and senior investigators, participate in seminars and
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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-dominated grids, protection systems, and wide-area dynamics. Scalable algorithms and numerical methods for large-scale simulation. Scientific software and software architectures for next-generation simulation
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, and development of algorithms for real-world clinical data. The fellow will have the opportunity to work with clinicians, engineers, data scientists, trainees, and research staff in a highly
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Qualifications · PhD or MD/PhD in neuroscience, molecular/cell biology, bioengineering, or a related field. · Demonstrated experience in extracellular vesicle exosome biology and advanced statistical analysis
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Employment 1.0 FTE Gross monthly salary € 3,706 - € 5,760 Required background PhD Organizational unit Faculty of Science Application deadline 14 October 2026 Apply now Join an ambitious
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● PhD (or foreign equivalent) in Applied Mathematics, Physics, Theoretical/Computational Biology
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, quantum science, condensed matter, materials, photonics and interdisciplinary applications of physical science. This role sits within a collaborative quantum science project at King’s on quantum algorithms
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects and mentoring. Contribute to academic publications
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. Responsibilities: Conduct research on automated reasoning and proof checker, AI-assisted collaboration. Develop and analyze algorithms for learning and optimization. Participate in collaborative research projects