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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
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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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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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primarily on structural analysis of protein complexes and will best suit a candidate with a PhD and relevant experience in protein biochemistry and structural biology, specifically cryo-EM/ET. The second post
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, challenging project. Learning on the job isn't just a benefit – it's a must. Education, Qualifications and Experience Essential Criteria Applicants should hold a PhD in a relevant area of Engineering
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for candidates to have the following skills and experience: Essential criteria PhD or equivalent experience in relevant area. Knowledge or interest in Natural Language Processing, ideally as applied to big
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ambitions We are seeking a candidate with: Educational background PhD in Architecture, Landscape Architecture, Computational Design, Computer Science, Urbanism, or a closely related field. Specialization in
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complex behaviours, including learning, in the small invertebrate model organism C. elegans. We have recently discovered a range of novel dopamine receptors in C. elegans and found that different receptors
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34 Faculty of Law Startdate: 15.09.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 14.09.2031 Reference no.: 4336 Explore and teach
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. Learn more about us here: https://swa.cs.univie.ac.at/ Your future tasks: You actively participate in research, teaching and administration, which means: You build up an independent research profile in