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international conferences on complex dynamical systems and related areas of mathematics. Besides your main research activities, you will teach one course per semester for most semesters while you are employed
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| Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.09.2029 Reference no.: 6194 Explore and teach at the University of Vienna, where more than 7,500 academics thrive
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and familiarity with at least one deep learning framework Basic understanding of NLP concepts (e.g., language models, tokenization, fine-tuning) Strong attention to detail, ability to follow
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experiments and policy-capturing methods may be used to compare interviewer judgements with evidence-based outcome measures. The project will also explore machine-learning, multimodal data analysis, computer
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considered a strong asset. Experience with Deep Learning and Artificial Intelligence is considered a plus. Excellent proficiency in the English language is required, as well as good communication skills, both
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(WEFE) nexus, and model-based learning and communication. The group makes use of a variety of tools and techniques: stakeholder mapping, governance analysis, participatory modeling, non-linear feedback
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remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is
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high-density 3D Multi-Electrode Arrays (3D-MEAs) — done in close collaboration with experts, providing full support as you learn to analyze this data. o Multi-Omic Profiling: Performing and analyzing