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field. • Msc in Mechanical Eng., Hydraulic/Civil Engineering, Chemical Eng., Physics, Math, Eng., Aeronautics or any corresponding Msc. • Knowledge of fluid mechanics. • Experience with
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.) Analytical mindset: You have a passion for solving complex problems and a solid foundation in math/stats/ML theory Teamwork and Communication: You enjoy interdisciplinary collaboration and are enthusiastic
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Junior Research Group “ Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible. The position is within the Math+ project "Information Flow
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the Leibniz Junior Research Group “ Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible. The position is within the Math+ project "Information Flow
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in Physics, Maths, Engineering, or a related discipline. Be familiar with differential equations and have some
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in Physics, Maths, Engineering, or a related discipline. Be familiar with differential equations and have some
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an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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. The position is within the Math+ project "Information Flow & Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and