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with multitarget estimation for direction-of-arrival (DOA) detection and tracking in radar theory [12]. Graphs are a powerful data structure to represent relational data and are widely used to describe
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nonstationarity, graph theory, machine learning and multivariate statistics; with applications in neuroscience, climate research, economics and general communication networks. More information about the group
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specialization. Requirements We are looking for candidates who have: Solid analytical and mathematical abilities Experience with machine learning Experience with formal language theory or automata theory Strong
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computer science, mathematics, statistics and/or probability theory. Support teaching at postgraduate level online. Moreover, you will: Have a good first degree or masters in a discipline relevant to computer
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-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be
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with expertise in Combinatorics and Graph Theory. DEPARTMENT: The mathematics program at Otterbein is unique in that mathematics majors begin, in their first semester, a study of advanced calculus and
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 2 months ago
. Project Description The successful candidate will work on the development of a Gaussian Process regression framework on graphs and its integration into: the Numerical Information Field Theory (NIFTy
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, lost/cost functions, stochastics, computational complexity, logic, graph theory or other areas closely related to it Proven expertise in techniques for descriptive statistics, vectors & matrices and
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15 Jan 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Mathematics » Statistics Researcher Profile First
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | about 1 month ago
interactions that proved powerful in other contexts. Hundreds of candidate variables can be combined together using a range of machine learning approaches, based on graph theory and on neural networks (in