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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
to work in the medical field • Good coding skills in Python • Fluent in English (Reading, Writing, Speaking) Contact People Send a CV and motivation leder to: maxime.sermesant@inria.fr, nadjia.kachenoura
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Research Division of Fred Hutch. Specific rank at the UW will be commensurate with experience and qualifications as generally described in UW's Faculty Code Section 24-34. Associate and full professors hold
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customers. Greets each customer in a friendly and courteous manner. Adheres to the department's dress code. Utilizes service recovery techniques as needed and informs the supervisor. Performs other related
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) 13 TV-L FU reference code: ONEMuc-FluBind2 The collaborative project ONEMUC – Respiratory Mucus as a One Health Interface investigates how the composition and structure of mucosal barriers (mucus
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) 13 TV-L FU reference code: ONEMuc_FluBind The collaborative project ONEMUC – Respiratory Mucus as a One Health Interface investigates how the composition and structure of mucosal barriers (mucus
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to identify coding and regulatory risk factors for early-onset, aggressive, and/or hereditary cancers The successful candidate will lead projects from conceptualization through publication, including
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of protein structure and conformationally dynamic systems.* Demonstrated interest in studying conformational free energy landscapes of biomolecules.* Strong programming and coding experience
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of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference code: 980 - 2026/WD 1
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Systems with a focus on Enzyme engineering (Reference code 37) Working time: 40 hours per week Term of the employment relationship: 1st of October 2026, limited to a period of 6 years Allocation in
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sequencing etc.) Expertise in at least one lineage of land plants (i.e., a taxonomic focus) Experience with at least one coding language or a strong background in statistics Experience with high-performance