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Field
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** Deployment and optimization of the PFAS analytical toolbox: targeted analyses (LC-MSMS, GC-MSMS), total oxidizable precursor assay (TOPFAS), and non-target screening (NTS, LC-HRMS Orbitrap). Intercomparison
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prediction metrics to optimize patient care. Identifying and addressing care gaps: Evaluating disparities in clinical management, assessing their impact and evaluating targeted interventions to improve them
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Requisition Id 15553 Overview: We are seeking a Postdoctoral researcher in data quality assessment and control and sensor network optimization who will focus on R&D of sensor network design. This
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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publication list Two educational or professional recommendations All documents must be in English or include an official English translation. Connect with ORISE...on the GO! Download the new ORISE GO mobile
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real scenarios; 3. Manufacture and test prototypes of optimized end plates using additive manufacturing, experimentally validating their mechanical, thermal, and electrochemical performance under
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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knowledge. The focus of the project can be defined in collaboration with the supervisor, with potential avenues including optimization aspects, parameter-efficient adaptation methods, model merging theory
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medicine, with a primary focus on optimizing clinical trial design. The partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry
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the assigned work in time. Complete complex research projects at different stages (advanced through nearly completed). Formulate, troubleshoot and optimize research methods and techniques as needed