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rotating patients who are unable to ambulate (up to 50 pounds). Special Conditions Must be approved by the Department of Corrections (DOC) and adhere to all DOC requirements. Posting Details Posting Number
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Post-Doc
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the interface of machine learning and biology (tools developed by the team: https://github.com/cantinilab). The team is composed of 8 people : 3PhD students, 3 post doc, 1 research engineer and 1 assistant
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 13 hours ago
Posting Details Posting Details Position Title 12-month Clinical Associate Professor, Master of Physician Assistant Studies External Link to Posting https://jobs.uncw.edu/postings/38742 College
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/Certification Advanced Practice Registered Nurse (APRN) or Physician Assistant-Certified (PA-C) with appropriate certification Physical Requirements Sitting at computer workstation for extended periods. Lifting
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/Certification Advanced Practice Registered Nurse (APRN) or Physician Assistant-Certified (PA-C) with appropriate certification Physical Requirements Sitting at computer workstation for extended periods. Lifting
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the interface of machine learning and biology (tools developed by the team: https://github.com/cantinilab ). The team is composed of 8 people : 3PhD students, 3 post doc, 1 research engineer and 1 assistant
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for testing machine learning algorithms applied to generative design in support of existing heritage regeneration processes. Where to apply E-mail reclutamento.docenti@ateneo.uniroma3.it Requirements Additional
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 25-Mar-26 Location: BOSTON, Massachusetts Internal Number: JR-2726 Research Associate/Technician Dana-Farber Cancer
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fellow to join our translational research program in macrophage biology/immunology. Our team takes a systems approach—integrating multi-omics, network science, machine learning, and comprehensive in vitro