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travel. Publish findings in high-impact journals and present at international conferences. Requirements: PhD or equivalent qualifications and experience in Analytical Chemistry, Chemical Engineering
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travel. Publish findings in high-impact journals and present at international conferences. Requirements: PhD or equivalent qualifications and experience in Analytical Chemistry, Chemical Engineering
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Center for Drug Evaluation and Research (CDER) | Saint Louis, Missouri | United States | 10 days ago
the resolution of conventional analytical methods, such as LC-UV and LC-UV/MS, to meet the escalating analytical demands. Robust and sensitive analytics leveraging modern technologies are imperative to advance
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Dutton Park campus About These Opportunities We are seeking two highly motivated and driven Postdoctoral Research Fellows, with expertise in the areas of environmental analytical chemistry and
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We are seeking a Research Associate/Fellow in Analytical Chemistry to transform the monitoring of pharmaceutical manufacturing and advancing sustainability through innovative automation, analytical
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years. Your main duties and areas of responsibility This PhD project addresses data analytics and optimization for routing and control of wind-assisted ships and is part of the WINTEGRATE (WIND+INTEGRATE
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duties and areas of responsibility This PhD project addresses data analytics and optimization for routing and control of wind-assisted ships and is part of the WINTEGRATE (WIND+INTEGRATE) project, which
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Stanford Securities Litigation Analytics is a research center within Stanford Law School focusing on public company shareholder litigation and corporate governance matters. SSLA closely collaborates with
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for Photon Science we are looking for a Postdoctoral Fellow in serial crystallography data analytics Your tasks The development of serial crystallography data analysis pipelines at SwissFEL and the SLS 2.0
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess