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significant role in working on a research project on machine learning modeling and optimization. Key Responsibilities: Development of new machine learning modelling approaches Development of new advanced
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geometry, optimization, and stochastic processes. Exceptional candidates in any field compatible with the research interests of the faculty are also encouraged to apply. Wesleyan University is a leading
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reimbursement, ambient clinical documentation, revenue cycle optimization, contact center and shared services automation), developing foundational structures to enable scalability and broad impact of the models
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, characterization, and development of peptide ligands for the purification of biological therapeutics. Supervise and maintain the equipment needed for ligand discovery and optimization. Collaborate with graduate
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selection, antibody optimization, and troubleshooting. Preferred Qualifications 3–5 years of experience in IHC (+/- IFC) techniques to include: image analysis, antibody handling and selection, antibody
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, governance, and optimization of these platforms. This role ensures seamless engagement across academic programs, philanthropy, alumni relations, human resources, and emerging applications in UK HealthCare
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assistance, scheduling, billing, claims follow-up, customer service and cash collection. The primary responsibility of staff within the Revenue Cycle is to optimally perform duties that ensure the collection
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collaboration across departments and levels Maintain open, consultative relationships to ensure optimal service and high-quality, cost-effective patient care Ensure regulatory compliance and reliable system
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to assist students, staff, and faculty. The ideal candidate will role model excellent educator and administrative skills, collaboration, communication, as well as thought leadership to optimize program
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infrastructure (routers, switches, firewalls, etc.) Troubleshoot and resolve complex network issues in a 24/7 environment Optimize performance and implement technologies like OSPF, BGP, IPv6, QoS, SNMP Document