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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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· PhD in Aerospace Engineering, Mechanical Engineering, Applied Physics, or a closely related discipline. · Strong academic background in computational mechanics, fluid dynamics, electromagnetics
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An exciting opportunity has arisen for a talented computer scientist to join our team as a researcher within the Green Algorithms Initiative in the Department of Public Health and Primary Care, one
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for funded Graduate Research Assistant (2-Master and 1-PhD positions) in the Flow Assurance Lab at Universiti Teknologi PETRONAS.The successful candidate will work on research related to multiphase flow
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, or a foreign degree considered on par with a doctoral degree. The ideal candidate holds a PhD degree in e.g Biomedical research or related subjects. In addition to formal competence, University
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Description Who We Are: The Cutsail research group at Ludwig-Maximilians-Universität (LMU) Munich is seeking a highly motivated PhD student / research assistant for full-time, on-site work in the
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) is advantageous Familiarity with scientific instrumentation and electronics What We Offer: TV-L (E13, 67%) collective agreement ( Current TV-L pay table [pdf-Datei] ) A three-year PhD contract Access
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candidate with a strong background in computational fluid dynamics (CFD) and specialized expertise in hemodynamics associated with coronary artery disease (CAD). The ideal candidate will hold a PhD in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
Requirements PhD in Pharmaceutical Sciences or directly related field Preferred Qualifications, Competencies, and Experience The Research Assistant Professor will have the following essential competencies
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Grant, focusing on the development of novel deep learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted