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Epic optimization or consolidation, large-scale IT integrations, and multi-entity organizational alignment Demonstrated results in digital transformation, including data analytics, clinical workflow
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 16 days ago
10 Dec 2025 Job Information Organisation/Company Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) Department Human Resources Research Field Medical sciences
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expertise in research and development in the following areas of AI and Data Science : Machine and deep learning, NLP, BDI (Belief-desire-intention) systems, and Large Language Models (LLMs). Expertise in
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for Future Networks & Communications, Insight - Centre for Data Analytics, Lero - Irish Software Research Centre, CONFIRM - Research Centre for Smart Manufacturing, and it is also hosting two large doctoral
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 8 days ago
, we believe that a combined effort between computer simulation, physics and mechanics is required. While computer simulation has developed a large amount of knowledge to efficiently solve large-scale
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on the genome of all living beings. Our group is mostly computational, and we do both large-scale data analysis and development of methods, but it has also an important experimental component. We participate in
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combination of education, experience, and training that would produce the required knowledge and abilities could be considered. Nature & Purpose of Position/Usual Duties: Supports and maintains computer
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: Vitaly Pryadka Web: http://www.phd-jobs.net Where to apply E-mail info@phd-jobs.net Requirements Research FieldMedical sciences » MedicineEducation LevelBachelor Degree or equivalent Additional Information
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scientists—on projects that bridge methods, policy, and practice. Position Description: This role will involve intensive analysis of claims data and related large administrative datasets to support policy
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, enterprise data modeling, or data engineering. Proven experience modernizing legacy data environments and designing cloud-native, AI-ready data architectures. Experience working with large, complex enterprise