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Field
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of mathematical modeling, with a particular focus on stochastic modeling, optimization and more recently machine learning. Indeed, over the last years, the team’s activity has been marked by a strong shift toward
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will be devoted to practical problems in economics and finance, like the construction of high-dimensional optimal portfolios. Motivated by the widespread application of sample generalized inverses in
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engineering Engineering » Mechanical engineering Engineering » Systems engineering Engineering » Other Environmental science » Other Mathematics » Applied mathematics Mathematics » Statistics Physics » Applied
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collaboration with experimental labs Profile Common requirements: PhD (completed or close to completion) in computer science, applied mathematics, computational neuroscience, robotics, physics or a closely
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Research Associate, Radiology and Imaging Services Posting Number req26573 Department Radiology & Imaging Sci Dept Department Website Link https://radiology.medicine.arizona.edu/ Location Tucson Campus
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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
Metabolic Flux Analysis (MFA), kinetic modeling, or constraint-based genome-scale modeling (COBRA). • Strong mathematical background in differential equations, linear algebra, and optimization. • Background
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expertise in network resilience or survivability and in network optimization. Solid programming skills (for example in Python) and hands on experience with mathematical optimization and network modelling. A
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4 Jul 2026 Job Information Organisation/Company AALTO UNIVERSITY Research Field Computer science Mathematics Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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3 Jul 2026 Job Information Organisation/Company CNRS Department Centre de Nanosciences et de Nanotechnologies Research Field Mathematics History » History of science Researcher Profile First Stage
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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