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to incorporate Large Language Models and/or other machine-learning (AI) tools into application code. Demonstrated attention to detail and accuracy Experience in Microsoft office products (Excel, Word) Preferred
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computational fluid dynamics. • Experience in modeling, uncertainty quantification, or statistical methods. • Experience in data science or machine learning is considered an asset. • Experience with high
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orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful
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AML. We integrate multi-omics profiling of patient primary samples with iPSC, organoid, and mouse models to define disease mechanisms and identify therapeutic vulnerabilities. Lab website: https
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research for the foreseeable future. There is a large interest from researchers, industry, and students. LIACS has a strong multidisciplinary AI portfolio (Machine Learning, Human-Computer Interaction
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Department of Computer Science of Faculty of Science invites applications for a DOCTORAL RESEARCHER IN MACHINE-LEARNING, STATISTICS AND DATA-CENTRIC ENGINEERING starting from September 2026, or as
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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Instruction Department's Website: https://cied.uark.edu/ Summary of Job Duties: The Department of Curriculum and Instruction in the College of Education and Health Professions at the University of Arkansas is
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maintenance of innovative teaching models and simulators—including the use of 3D printing and custom-built designs—to enhance experiential learning in the clinical skills laboratory. In addition, you will
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paired with computational biology and machine learning to develop predictive AI models of how cells interpret and respond to the surrounding extracellular matrix. Required Qualifications: We are looking