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data analysis. The successful candidate will also be involved in the preparation of samples and their characterization using standard laboratory-based methods (optical and scanning electron microscopy
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research consortium will develop a new type of molecular motor, based on a proto-driven switching mechanism, called tautomerism, which has thus far remained underexplored in motor designs, despite its
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Previous experience with in vivo animal models is advantageous Excellent communication skills in English (oral and written) are a must High motivation, strong interest in skeletal research, durability
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research. Your position Design, implement, and evaluate large-language-model (LLM) pipelines for synthetic data (fine-tuning, retrieval-augmented generation [RAG], prompt engineering). Plan and analyze
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utilization. The successful candidate will play a significant role in the EU‑funded TIMBERHAUS project (www.timberhaus.eu). Your tasks Develop machine learning models and computer vision algorithms for wood
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responsibility for our unique GPU-accelerated 3D FDTD software suite and extending its capabilities Modelling the effects of atmospheric turbulence fields Software development (3D modelling and coding in Python, C
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thinking with renewable energy community planning, developing methodological innovations that bridge quantitative modeling and qualitative approaches. Your tasks Develop and apply optimization and simulation
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-collection costs while maintaining validity for marketing and opinion research. Design, implement, and evaluate large-language-model (LLM) pipelines for synthetic data (fine-tuning, retrieval-augmented
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epithelium. We make use of state-of-the-art in vivo and in vitro organoid and microbiota models, omics techniques and bioengineering approaches to dissect cellular crosstalk in the intestinal mucosa in
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/current sources dedicated towards the research question. Measured data is thoroughly analyzed with state-of-the-art theoretical models and published fully open access. The aim of our research is to advance