395 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions in United Kingdom
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settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems, attack surfaces
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vitro, organoid co-culture models will be developed using primary human epithelial cells. Candidates should have an excellent research track record, be committed to the project and keen to work in a
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We are looking for a postdoc candidate to lead an innovative research project that integrates kinetochore biology with neuroscience. This project builds on the pioneering discoveries made by
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We are seeking a Postdoctoral Research Associate to support our projects to understand membrane evolution. The aim of this project is to use molecular dynamic simulations to understand membrane
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the successful software package VASP (Vienna ab-initio Simulation Package). Currently, the group consists of two full professors, one associate professor, several postdocs and about 10 PhD and master students
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-rata) for professional development. This entitlement, from the Concordat to Support the Career Development of Researchers , applies to Postdocs, Research Assistants, Research and Teaching Technicians
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information to specialists and within the wider academic community. Experience in designing and operating combustion test rigs; developing analytical engineering models using CONVERGE or other CFD tools; and
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concept of agents has come to the fore again, prompted by the rise of Large Language Models (LLMs) – put crudely, the idea is to use LLMs, in the sense of being powerful general purpose intelligent systems
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40 Faculty of Historical and Cultural Studies Startdate: 01.10.2025 | Working hours: 20 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: permanent Reference no.: 4410
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models