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-renowned research institute and work closely with PhD students, PostDocs, software engineers and faculty members on developing cutting-edge AI ready data management. We’re working on extending and
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available. In parallel, we prospectively collect skin biopsies from well-phenotyped Parkinson patients (ProPARK cohort). We generate well-defined iPSC. Using advanced genomics and proteomics we aim
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collaboration with leading industrial and academic partners within large-scale Horizon Europe initiatives, where LTU plays a key role in both technical development and scientific coordination. In parallel with
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reports Develop and apply software tools Document software and data according to the FAIR data principles Contribute to workshops and training activities Your Profile: Master with subsequent PhD degree in
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scientific results in peer-reviewed journals or conferences. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related discipline completed within the last five
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developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation of results. Deliver ORNL’s mission by aligning
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techniques for the generation and exploration of complex, large-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable
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other domain experts to facilitate collaboration. Present and report research results and publish scientific results in peer-reviewed journals or conferences. Basic Qualifications: A PhD in Computer
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mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Basic Qualifications: PhD in a computational discipline such as Data
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activities. Your Profile: Master and PhD degree in astronomy, physics, computer science or equivalent fields of study. Proven experience in N-body simulations and the comparison of simulation and observation