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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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applicant must have passed courses within the first and second cycles of at least 90 credits in either, a) Chemistry/Molecular Biology/Biotechnology, or b) Computer Science/Mathematics/Physics and at
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, Mexico City 04510, Mexico [map ] Subject Area: Probability Appl Deadline: 2025/05/30 11:59PM (posted 2025/04/11, listed until 2025/05/30) Position Description: Apply Position Description The Instituto de
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density matter , High Energy Experimental , High Energy Physics , high energy physics or mathematical physics , High Energy Theory , High Energy Theory Group , High Performance Computing , Holographic
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Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research, or Economics Analytical problem-solvers with
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systems Documented knowledge in power and energy markets preferably Nordic and European markets Documented knowledge in dynamic modelling of power system Knowledge of mathematical optimization. Knowledge
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. Your job In this PhD position, you will conduct idealised experiments with an atmospheric model (OpenIFS), using concepts from the mathematical field of periodically forced dynamical systems. You will
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work may suit applicants from a mathematics, computer science, or data science background. A demonstrable understanding of, and passion for, psychological research is essential. Candidates should be able
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in both research and education with other UCL departments, including computer science, engineering, economics, psychology, public policy, statistics and medical sciences. About the role The UCL School