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Postdoctoral Fellow - Materials Chemistry, Texas Materials Institute, Cockrell School of Engineering
or parallel reactors Collaborate with computational scientists to integrate machine-learning models for closed-loop materials discovery Collaborate with companion postdocs on functional materials
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21 Nov 2025 Job Information Organisation/Company University of Beira Interior Department Informatics Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1
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) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Heikkilä at Jyväskylä University. In parallel, the NANO group is pursuing work on fractional Chern insulator in twisted TMD materials. Since there is clear synergy between twisted graphene and twisted TMD
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(End Date of Assignment, Project, or Grant) 09/30/2026 Position Type Faculty Job Family Faculty Position Overview Computational Combustion Laboratory (CCL) at Marquette University is recruiting a
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The National Energy Research Scientific Computing Center (NERSC ) at Berkeley Lab seeks a highly motivated Postdoctoral Researcher — Scientific Machine Learning (NESAP) to join the Workflow
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- 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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for large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with
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and broadcasting systems and has developed the best-in-class large scale testbeds for research and innovation and enjoys the state-of-the-art lab and computing facilities. Established in 2012, 5GIC is
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, reproducible computational workflows for large-scale screening and multiscale model integration. HPC at Scale: Run, optimize, and profile large simulations on HPC systems; ensure efficient parallel performance