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matching post based at Teesside University); (3) nature and natural heritage (the focus of a matching post based at Newcastle University); (4) active evaluation for learning (e.g. research conducted by team
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reasons to research and teach at the University of Vienna there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities who need space for
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of the "Interdisciplinary Values Research Network". You apply for projects and raise third-party funds. You teach classes independently and supervise students. You are involved in evaluation measures and quality management
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instrumentation. Essential profile: Applicants must hold a PhD in Physics (or a closely related discipline) and demonstrate substantial, hands-on experience in optical design and advanced microscopy development
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no.: 4135 Explore and teach at the University of Vienna, where over 7,500 academic minds have found a unique blend of freedom and support. Join us if you're driven by a passion for top-notch international
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research findings. Analyse and interpret research results and findings from the project, using automatic methods with appropriate software. Supervise and teach other members of the research team (e.g. Master
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the development of hierarchical computational materials discovery schemes combining random structure searching, machine learning, atomistic, and density functional theory (DFT) calculations to accurately and
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51 Faculty of Physics Startdate: 01.09.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.08.2028 Reference no.: 4121 Explore and teach
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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
for isomerization in MOFs: https://doi.org/10.1039/D3QI01065A What we are looking for: A PhD in Chemistry, Materials Science, Physics or a related field Experience in python (ASE, scikit-learn, pytorch) is essential