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2 Apr 2026 Job Information Organisation/Company Personalabteilung der Montanuniversität Leoben Research Field All Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 7 hours ago
collaborate closely with Professor Colin Meyer at Dartmouth College to develop new models of polynya dynamics, efficient algorithms for inversion of surface signatures, and deeper understanding of controls
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-2, PRISMA, EnMAP) data for showcasing the improved mapping and monitoring of forest traits and uncertainties. You will be mainly in charge of: Develop improved hybrid model inversion methods with a
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21 Mar 2026 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Geosciences Researcher Profile Established Researcher (R3) Application Deadline 24 Apr 2026
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25 Mar 2026 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Environmental science » Earth science Researcher Profile First Stage Researcher (R1
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Information Science (GIS), and computational science for health and environment, to study processes spanning from the microscopic to the planetary, across all time scales. The Inverse Modelling group at the Department
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with advanced statistical techniques (optimal Bayesian, Markov Chain-Monte Carlo, etc.) to solve the forward and inverse problems involved. Additional information about AGAGE, CS3, and MIT atmospheric chemistry
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling
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membrane design, as well as advanced membrane fabrication techniques utilizing electrospinning, phase inversion, and additive manufacturing. The researcher will also develop robust pretreatment processes (MF
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. Richard Nickl and work in the project area 'Statistical aspects of non-linear inverse problems', which broadly addresses mathematical and foundational challenges in contemporary data science and the theory