11 computational-complexity-"U" Postdoctoral positions at Purdue University in United States
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-house CFD software packages. (3) Designing and developing CFD sub-models for application to a broad range of CFD problems. (4) Using high-performance computing (HPC) to accelerate complex, large-scale
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, with frequent travel to campus, may be available. We are recruiting multiple postdocs to join our team in this role. Responsibilities and Duties: Develop and implement complex data analysis projects
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candidate must excel in critical thinking and be adept at designing and executing complex research studies. While data analysis skills are beneficial, they will work closely with data analysts and
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Purdue’s strategic focus on health equity and population health. Program Goals and Learning Objectives The fellow will gain experience in: Designing and conducting pharmacoepidemiologic studies in cancer and
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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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using R for statistical analysis and in statistical modeling. Sound working knowledge of unix shell, high performance compute clusters and git. Willingness to learn and use a scripting language (e.g
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Job Description Apply now Req Id: 37108 Job Title: Post Doc Research Assistant City: West Lafayette Job Description: Job Summary A postdoc position is available immediately in Andrew DeWoody’s lab at Purdue University (West Lafayette, Indiana, USA). The successful applicant will develop,...
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discussions for other timelines are possible. Qualifications: PhD in a broadly related field (e.g., cognitive science, computer science, psychology, learning sciences, linguistics, speech-language-hearing
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communication skills. Strong attention to detail and good organizational skills. Strong desire to work in a collaborative research program. Interested candidates should email Professor Michael Manfra at mmanfra